Search Images Maps Play YouTube News Gmail Drive More »
Sign in
Screen reader users: click this link for accessible mode. Accessible mode has the same essential features but works better with your reader.

Patents

  1. Advanced Patent Search
Publication numberUS9270299 B2
Publication typeGrant
Application numberUS 13/025,900
Publication date23 Feb 2016
Filing date11 Feb 2011
Priority date11 Feb 2011
Also published asCN103444087A, EP2673885A1, US20120210190, WO2012109614A1
Publication number025900, 13025900, US 9270299 B2, US 9270299B2, US-B2-9270299, US9270299 B2, US9270299B2
InventorsMichael G. Luby, Payam Pakzad, Mohammad Amin Shokrollahi, Mark Watson, Lorenzo Vicisano
Original AssigneeQualcomm Incorporated
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Encoding and decoding using elastic codes with flexible source block mapping
US 9270299 B2
Abstract
Data can be encoded by assigning source symbols to base blocks, assigning base blocks to source blocks and encoding each source block into encoding symbols, where at least one pair of source blocks is such they have at least one base block in common with both source blocks of the pair and at least one base block not in common with the other source block of the pair. The encoding of a source block can be independent of content of other source blocks. Decoding to recover all of a desired set of the original source symbols can be done from a set of encoding symbols from a plurality of source blocks wherein the amount of encoding symbols from the first source block is less than the amount of source data in the first source block and likewise for the second source block.
Images(6)
Previous page
Next page
Claims(51)
The invention claimed is:
1. A method for encoding data to be transmitted from an electronic device or system to a receiver over a communications channel that could possibly introduce errors or erasures, wherein source data is represented by an ordered plurality of source symbols and the source data is recoverable from encoding symbols that are transmitted, the method comprising:
identifying a base block for each source symbol of the ordered plurality of source symbols, wherein the identified base block is one of a plurality of base blocks that, collectively, cover the source data to be encoded;
identifying, from a plurality of source blocks and for each base block, at least one source block that envelops that base block, wherein the plurality of source blocks includes at least one pair of source blocks that have a characteristic that there is at least one base block that is enveloped by both source blocks of the pair and at least one base block for each source block of the pair that is enveloped by that source block and not by the other source block of the pair;
encoding each of the plurality of source blocks according to an encoding process, resulting in encoding symbols, wherein the encoding process operates on one source block to generate encoding symbols, with the encoding symbols being independent of source symbol values of source symbols from base blocks not enveloped by the one source block, wherein the encoding is such that a portion of the source data that is represented by a union of the pair of source blocks is assured to be recoverable from a combination of a first set of encoding symbols generated from a first source block of the pair and a second set of encoding symbols generated from a second source block of the pair, wherein an amount of encoding symbols in the first set is less than an amount of source data in the first source block and an amount of encoding symbols in the second set is less than an amount of source data in the second source block; and
outputting the encoding symbols for transmission to the receiver over the communications channel.
2. The method of claim 1, wherein the encoding process is such that, when the encoding symbols and the source symbols have a same size, when the first set of encoding symbols comprises M1 encoding symbols, the first source block comprises N1 source symbols, the second set of encoding symbols comprises M2 encoding symbols, the second source block comprises N2 source symbols, and when an intersection of the first and second source blocks comprises N3 source symbols with N3 greater than zero, then recoverability of the union of the pair of source blocks is assured beyond a predetermined threshold probability if M1+M2=N1+N2−N3 for at least some combinations of values of M1<N1 and M2<N2.
3. The method of claim 2, wherein the recoverability of the union of the pair of source blocks is assured beyond a predetermined threshold probability if M1+M2=N1+N2−N3 for all combinations of values of M1 and M2 such that M1≦N1 and M2≦N2.
4. The method of claim 2, wherein the recoverability of the union of the pair of source blocks is certain if M1+M2=N1+N2−N3 for all combinations of values of M1 and M2 such that M1≦N1 and M2≦N2.
5. The method of claim 2, wherein the recoverability of the union of the pair of source blocks is assured with a probability higher than a predetermined threshold probability if M1+M2 is larger than N1+N2−N3 by less than a predetermined percentage but smaller than N1+N2 for at least some combinations of values of M1 and M2.
6. The method of claim 1, wherein at least one encoding symbol generated from a source block is equal to a source symbol from a portion of the source data that is represented by that source block.
7. The method of claim 1, wherein the encoding process is such that a portion of the source data that is represented by the first source block of the pair is assured to be recoverable from a third set of encoding symbols generated from the first source block, wherein an amount of encoding symbols in the third set is no greater than the amount of source data in the first source block.
8. The method of claim 1, wherein the encoding process is such that a portion of the source data that is represented by the first source block of the pair is assured to be recoverable with a probability higher than a predetermined threshold probability from a third set of encoding symbols generated from the first source block, wherein an amount of encoding symbols in the third set is only slightly greater than the amount of source data in the first source block.
9. The method of claim 1, wherein a number of distinct encoding symbols that can be generated from each source block is independent of a size of the source block.
10. The method of claim 1, wherein a number of distinct encoding symbols that can be generated from each source block depends on a size of the source block.
11. The method of claim 1, wherein identifying base blocks for source symbols is performed prior to a start to encoding.
12. The method of claim 1, wherein identifying source blocks for base blocks is performed prior to a start to encoding.
13. The method of claim 1, wherein at least one encoding symbol is generated before a base block is identified for each source symbol or before the enveloped base blocks are determined for each of the source blocks or before all of the source data is generated or made available.
14. The method of claim 1, further comprising:
receiving receiver feedback representing results at a decoder that is receiving or has received encoding symbols; and
adjusting one or more of membership of source symbols in base blocks, membership of base blocks in enveloping source blocks, number of source symbols per base block, number of symbols in a source block, and/or number of encoding symbols generated from a source block, wherein the adjusting is done based on, at least in part, the receiver feedback.
15. The method of claim 14, wherein adjusting includes determining new base blocks or changing membership of source symbols in previously determined base blocks.
16. The method of claim 14, wherein adjusting includes determining new source blocks or changing envelopment of base blocks for previously determined source blocks.
17. The method of claim 1, further comprising:
receiving data priority preference signals representing varying data priority preferences over the source data; and
adjusting one or more of membership of source symbols in base blocks, membership of base blocks in enveloping source blocks, number of source symbols per base block, number of symbols in a source block, and/or number of encoding symbols generated from a source block, wherein the adjusting is done based on, at least in part, the data priority preference signals.
18. The method of claim 1, wherein a number of source symbols in the base blocks enveloped by each source block is independent, as between two or more of the source blocks.
19. The method of claim 1, wherein source symbols identified to a base block are not consecutive within the ordered plurality of source symbols.
20. The method of claim 1, wherein source symbols identified to a base block are consecutive within the ordered plurality of source symbols.
21. The method of claim 20, wherein source symbols identified to the base blocks enveloped by a source block are consecutive within the ordered plurality of source symbols.
22. The method of claim 1, wherein a number of encoding symbols that can be generated for a source block is independent of a number of encoding symbols that can be generated for other source blocks.
23. The method of claim 1, wherein a number of encoding symbols generated for a given source block is independent of a number of source symbols in base blocks enveloped by the given source block.
24. The method of claim 1, wherein encoding further comprises:
determining, for each encoding symbol, a set of coefficients selected from a finite field; and
generating the encoding symbol as a combination of source symbols of one or more base blocks enveloped by a single source block, wherein the combination is defined, in part, by the set of coefficients.
25. The method of claim 1, wherein a number of symbol operations to generate an encoding symbol from a source block is linearly proportional to a number of source symbols in a portion of the source data that is represented by the source block.
26. A method for decoding data received at an electronic device or system and delivered from a transmitter over a communications channel that could possibly include errors or erasures, to recover source data that was represented by a set of source symbols, the method comprising:
identifying a base block for each source symbol, wherein the identified base block is one of a plurality of base blocks that, collectively, cover the source data;
identifying, from a plurality of source blocks and for each base block, at least one source block that envelops that base block, wherein the plurality of source blocks includes at least one pair of source blocks that have a characteristic that there is at least one base block that is enveloped by both source blocks of the pair and at least one base block for each source block of the pair that is enveloped by that source block and not by the other source block of the pair; and
receiving a plurality of received symbols;
for each received symbol, identifying a source block for which that received symbol is an encoding symbol for;
decoding a set of source symbols from the plurality of received symbols, wherein a portion of the source data that is represented by a union of the pair of source blocks is assured to be recoverable from a combination of a first set of received symbols corresponding to encoding symbols that were generated from a first source block of the pair and a second set of received symbols corresponding to encoding symbols that were generated from a second source block of the pair, wherein an amount of received symbols in the first set is less than an amount of source data in the first source block and an amount of received symbols in the second set is less than an amount of source data in the second source block; and
outputting the decoded source symbols in a computer-readable form.
27. The method of claim 26, wherein if N1 is a number of source symbols in source data of the first source block, if N2 is a number of source symbols in source data of the second source block, if N3 is a number of source symbols in an intersection of the first and second source blocks with N3 greater than zero, if the encoding symbols and the source symbols have a same size, if R1 is a number of received symbols in the first set of received symbols, if R2 is a number of received symbols in the second set of received symbols, then decoding the union of the pair of source blocks from the first set of R1 received symbols and from the second set of R2 received symbols is assured beyond a predetermined threshold probability if R1+R232 N1+N2 −N3, for at least one value of R1 and R2 such that R1<N1 and R2<N2.
28. The method of claim 27, wherein decoding the union of the pair of source blocks is assured beyond a predetermined threshold probability if R1+R2=N1+N2−N3 for all values of R1≦N1 and R2≦N2.
29. The method of claim 27, wherein decoding the union of the pair of source blocks is certain if R1+R2=N1+N2−N3 for all values of R1≦N1 and R2≦N2.
30. The method of claim 26, wherein a portion of the source data that is represented by the first source block of the pair is recoverable from a third set of encoding symbols generated from the first source block, wherein an amount of encoding symbols in the third set is no greater than the amount of source data in the first source block.
31. The method of claim 26, wherein a number of distinct encoding symbols that can be generated from each source block is independent of a size of the source block.
32. The method of claim 26, wherein at least one of identifying base blocks for source symbols and identifying source blocks for base blocks is performed prior to a start to decoding.
33. The method of claim 26, wherein at least some source symbols are decoded before a base block is identified for each source symbol and/or before the enveloped base blocks are determined for each of the source blocks.
34. The method of claim 26, further comprising:
determining receiver feedback representing results at a decoder based on what received symbols have been received and/or what portion of the source data is desired at a receiver and/or data priority preference; and
outputting the receiver feedback such that it is usable for altering an encoding process.
35. The method of claim 26, wherein a number of source symbols in the base blocks enveloped by each source block is independent, as between two or more of the source blocks.
36. The method of claim 26, wherein source symbols identified to a base block are consecutive within an ordered plurality of source symbols that is the set of source symbols.
37. The method of claim 26, wherein source symbols identified to the base blocks enveloped by a source block are consecutive within an ordered plurality of source symbols that is the set of source symbols.
38. The method of claim 26, wherein decoding further comprises:
determining, for each received symbol, a set of coefficients selected from a finite field; and
decoding at least one source symbol from more than one received symbol or previously decoded source symbols using the set of coefficients for the more than one received symbol.
39. The method of claim 26, wherein a number of symbol operations to recover a union of one or more source blocks is linearly proportional to a number of source symbols in a portion of the source data that is represented by the union of one or more source blocks.
40. An encoder of an electronic device or system that encodes data for transmission to a receiver over a communications channel that could possibly introduce errors or erasures, comprising:
an input for receiving source data that is represented by an ordered plurality of source symbols and the source data is recoverable from encoding symbols that are transmitted;
storage for at least a portion of a plurality of base blocks, wherein each base block comprises a representation of one or more source symbols of the ordered plurality of source symbols;
a logical map, stored in a machine-readable form or generatable according to logic instructions, mapping each of a plurality of source blocks to one or more base blocks, wherein the plurality of source blocks includes at least one pair of source blocks that have a characteristic that there is at least one base block that is enveloped by both source blocks of the pair and at least one base block for each source block of the pair that is enveloped by that source block and not by the other source block of the pair;
storage for encoded blocks;
one or more encoders that each encode source symbols of a source block to form a plurality of encoding symbols, with a given encoding symbol being independent of source symbol values from source blocks other than the source block it encodes source symbols of, such that a portion of the source data that is represented by a union of the pair of source blocks is assured to be recoverable from a combination of a first set of encoding symbols generated from a first source block of the pair and a second set of encoding symbols generated from a second source block of the pair, wherein an amount of encoding symbols in the first set is less than an amount of source data in the first source block and an amount of encoding symbols in the second set is less than an amount of source data in the second source block; and
an output for outputting the encoding symbols for transmission to the receiver over the communications channel.
41. The encoder of claim 40, wherein a number of encoding symbols in the first set plus a number of encoding symbols in the second set is no greater than a number of source symbols in the portion of the source data that is represented by the union of the pair of source blocks, if the encoding symbols and the source symbols have a same size.
42. The encoder of claim 40, wherein a portion of the source data that is represented by the first source block of the pair is recoverable from a third set of encoding symbols generated from the first source block, wherein an amount of encoding symbols in the third set is no greater than the amount of source data in the first source block.
43. The encoder of claim 40, wherein a number of distinct encoding symbols that can be generated from each source block is independent of a size of the source block.
44. The encoder of claim 40, further comprising:
an input for receiving receiver feedback representing results at a decoder that is receiving or has received encoding symbols; and
logic for adjusting one or more of membership of source symbols in base blocks, membership of base blocks in enveloping source blocks, number of source symbols per base block, number of symbols in a source block, and/or number of encoding symbols generated from a source block, wherein the adjusting is done based on, at least in part, the receiver feedback.
45. The encoder of claim 40, further comprising:
an input for receiving data priority preference signals representing varying data priority preferences over the source data; and
logic for adjusting one or more of membership of source symbols in base blocks, membership of base blocks in enveloping source blocks, number of source symbols per base block, number of symbols in a source block, and/or number of encoding symbols generated from a source block, wherein the adjusting is done based on, at least in part, the data priority preference signals.
46. The encoder of claim 40, wherein a number of source symbols in the base blocks enveloped by each source block is independent, as between two or more of the source blocks.
47. The encoder of claim 40, wherein source symbols identified to a base block are consecutive within the ordered plurality of source symbols.
48. The encoder of claim 40, wherein source symbols identified to the base blocks enveloped by a source block are consecutive within the ordered plurality of source symbols.
49. The encoder of claim 40, wherein a number of distinct encoding symbols that can be generated for a source block is independent of a number of encoding symbols that can be generated for other source blocks.
50. The encoder of claim 40, wherein a number of distinct encoding symbols generated for a given source block is independent of a number of source symbols in base blocks enveloped by the given source block.
51. The encoder of claim 40, further comprising:
storage for a set of coefficients selected from a finite field for each of a plurality of the encoding symbols, wherein the one or more encoders further comprise
logic for generating the encoding symbol as a combination of source symbols of one or more base blocks enveloped by a single source block, wherein the combination is defined, in part, by the set of coefficients.
Description
CROSS REFERENCES

The Present Application for Patent is related to the following co-pending U.S. Patent Applications, each of which is filed concurrently herewith, assigned to the assignee hereof, and expressly incorporated by reference herein:

U.S. Patent Application entitled “Framing for an Improved Radio Link Protocol Including FEC” by Mark Watson, et al., having Ser. No. 13/025,925; and

U.S. Patent Application entitled “Forward Error Correction Scheduling for an Improved Radio Link Protocol” by Michael G. Luby, et al., having Ser. No. 13/025,934.

The following issued patents are expressly incorporated by reference herein for all purposes:

U.S. Pat. No. 6,909,383 entitled “Systematic Encoding and Decoding of Chain Reaction Codes” to Shokrollahi et al. issued Jun. 21, 2005 (hereinafter “Shokrollahi-Systematic”); and

U.S. Pat. No. 6,856,263 entitled “Systems and Processes for Decoding Chain Reaction Codes Through Inactivation” to Shokrollahi et al. issued Feb. 15, 2005 (hereinafter “Shokrollahi-Inactivation”).

BACKGROUND

1. Field

The present disclosure relates in general to methods, circuits, apparatus and computer program code for encoding data for transmission over a channel in time and/or space and decoding that data, where erasures and/or errors are expected, and more particularly to methods, circuits, apparatus and computer program code for encoding data using source blocks that overlap an can be partially or wholly coextensive with other source blocks.

2. Background

Transmission of files between a sender and a recipient over a communications channel has been the subject of much literature. Preferably, a recipient desires to receive an exact copy of data transmitted over a channel by a sender with some level of certainty. Where the channel does not have perfect fidelity (which covers most all physically realizable systems), one concern is how to deal with data lost or garbled in transmission. Lost data (erasures) are often easier to deal with than corrupted data (errors) because the recipient cannot always tell when corrupted data is data received in error. Many error correcting codes have been developed to correct for erasures and/or for errors. Typically, the particular code used is chosen based on some information about the infidelities of the channel through which the data is being transmitted and the nature of the data being transmitted. For example, where the channel is known to have long periods of infidelity, a burst error code might be best suited for that application. Where only short, infrequent errors are expected a simple parity code might be best.

In particular applications, there is a need for handling more than one level of service. For example, a broadcaster might broadcast two levels of service, wherein a device capable of receiving only one level receives an acceptable set of data and a device capable of receiving the first level and the second level uses the second level to improve on the data of the first level. An example of this is FM radio, where some devices only received the monaural signal and others received that and the stereo signal. One characteristic of this scheme is that the higher layers are not normally useful without the lower layers. For example, if a radio received the secondary, stereo signal, but not the base signal, it would not find that particularly useful, whereas if the opposite occurred, and the primary level was received but not the secondary level, at least some useful signal could be provided. For this reason, the primary level is often considered more worthy of protection relative to the secondary level. In the FM radio example, the primary signal is sent closer to baseband relative to the secondary signal to make it more robust.

Similar concepts exist in data transport and broadcast systems, where a first level of data transport is for a basic signal and a second level is for an enhanced layer. An example is H.264 Scalable Video Coding (SVC) wherein an H.264 base compliant stream is sent, along with enhancement layers. An example is a 1 megabit per second (mbps) base layer and a 1 mbps enhancement layer. In general, if a receiver is able to decode all of the base layer, the receiver can provide a useful output and if the receiver is able to decode all of the enhancement layer the receiver can provide an improved output, however if the receiver cannot decode all of the base layer, decoding the enhancement layer does not normally provide anything useful.

Forward error correction (“FEC”) is often used to enhance the ability of a receiver to recover data that is transmitted. With FEC, a transmitter, or some operation, module or device operating for the transmitter, will encode the data to be transmitted such that the receiver is able to recover the original data from the transmitted encoded data even in the presence of erasures and or errors.

Because of the differential in the effects of loss of one layer versus another, different coding might be used for different layers. For example, the data for a base layer might be transmitted with additional data representing FEC coding of the data in the base layer, followed by the data of the enhanced layer with additional data representing FEC coding of the data in the base layer and the enhanced layer. With this approach, the latter FEC coding can provide additional assurances that the base layer can be successfully decoded at the receiver.

While such a layered approach might be useful in certain applications, it can be quite limiting in other applications. For example, the above approach can be impractical for efficiently decoding a union of two or more layers using some encoding symbols generated from one of the layers and other encoding symbols generated from the combination of the two or more layers.

SUMMARY

Data can be encoded by assigning source symbols to base blocks, assigning base blocks to source blocks and encoding each source block into encoding symbols, where at least one pair of source blocks is such they have at least one base block in common with both source blocks of the pair and at least one base block not in common with the other source block of the pair. The encoding of a source block can be independent of content of other source blocks. Decoding to recover all of a desired set of the original source symbols can be done from a set of encoding symbols from a plurality of source blocks wherein the amount of encoding symbols from the first source block is less than the amount of source data in the first source block and likewise for the second source block.

In specific embodiments, an encoder can encode source symbols into encoding symbols and a decoder can decode those source symbols from a suitable number of encoding symbols. The number of encoding symbols from each source block can be less than the number of source symbols in that source block and still allow for complete decoding.

In a more specific embodiment where a first source block comprises a first base block and a second source block comprises the first base block and a second base block, a decoder can recover all of the first base block and second base block from a set of encoding symbols from the first source block and a set of encoding symbols from the second source block where the amount of encoding symbols from the first source block is less than the amount of source data in the first source block, and likewise for the second source block, wherein the number of symbol operations in the decoding process is substantially smaller than the square of the number of source symbols in the second source block.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a communications system that uses elastic codes according to aspects of the present invention.

FIG. 2 is a block diagram of an example of a decoder used as part of a receiver that uses elastic codes according to aspects of the present invention.

FIG. 3 illustrates, in more detail, an encoder, which might be the encoder shown in FIG. 1, or one encoder unit in an encoder array.

FIG. 4 illustrates an example of a source block mapping according to elastic codes.

FIG. 5 illustrates an elastic code that is a prefix code and G=4.

FIG. 6 illustrates an operation with a repair symbol's block.

Attached as Appendix A is a paper presenting Slepian-Wolf type problems on an erasure channel, with a specific embodiment of an encoder/decoder system, sometimes with details of the present invention used, which also includes several special cases and alternative solutions in some practical applications, e.g., streaming. It should be understood that the specific embodiments described in Appendix A are not limiting examples of the invention and that some aspects of the invention might use the teachings of Appendix A while others might not. It should also be understood that limiting statements in Appendix A may be limiting as to requirements of specific embodiments and such limiting statements might or might not pertain the claimed inventions and, therefore, the claim language need not be limited by such limiting statements.

To facilitate understanding, identical reference numerals have been used where possible to designate identical elements that are common to the figures, except that suffixes may be added, where appropriate, to differentiate such elements. The images in the drawings are simplified for illustrative purposes and are not necessarily depicted to scale.

The appended drawings illustrate exemplary configurations of the disclosure and, as such, should not be considered as limiting the scope of the disclosure that may admit to other equally effective configurations. Correspondingly, it has been contemplated that features of some configurations may be beneficially incorporated in other configurations without further recitation.

DETAILED DESCRIPTION

The present invention is not limited to specific types of data being transmitted. However in examples herein, it will be assumed that the data could be transmitted is represented by a sequence of one or more source symbols and that each source symbol has a particular size, sometimes measured in bits. While it is not a requirement, in these examples, the source symbol size is also the size of encoding symbols. The “size” of a symbol can be measured in bits, whether or not the symbol is actually broken into a bit stream, where a symbol has a size of M bits when the symbol is selected from an alphabet of 2M symbols.

In the terminology used herein, the data to be conveyed is represented by a number of source symbols, where K is used to represent that number. In some cases, K is known in advance. For example, when the data to be conveyed is a file of unknown size and an integer multiple of the source symbol size, K would simply be the integer that is that multiple. However, it might also be the case that K is not known in advance of the transmission, or is not known until after the transmission has already started. For example, where the transmitter is transmitting a data stream as the transmitter receives the data and does not have an indication of when the data stream might end.

An encoder generates encoding symbols based on source symbols. Herein, the number of encoding symbols is often referred to as N. Where N is fixed given K, the encoding process has a code rate, r=K/N. Information theory holds that if all source symbol values are equally possible, perfect recovery of the K source symbols requires at least K encoding symbols to be received (assuming the same size for source symbols and encoding symbols) in order to fully recover the K source symbols. Thus, the code rate using FEC is usually less than one. In many instances, lower code rates allow for more redundancy and thus more reliability, but at a cost of lower bandwidth and possibly increased computing effort. Some codes require more computations per encoding symbol than others and for many applications, the computational cost of encoding and/or decoding will spell the difference between a useful implementation and an unwieldy implementation.

Each source symbol has a value and a position within the data to be transmitted and they can be stored in various places within a transmitter and/or receiver, computer-readable memory or other electronic storage, that contains a representation of the values of particular source symbols. Likewise, each encoding symbol has a value and an index, the latter being to distinguish one encoding symbol from another, and also can be represented in computer- or electronically-readable form. Thus, it should be understood that often a symbol and its physical representation can be used interchangeably in descriptions.

In a systematic encoder, the source symbols are part of the encoding symbols and the encoding symbols that are not source symbols are sometimes referred to as repair symbols, because they can be used at the decoder to “repair” damage due to losses or errors, i.e., they can help with recovery of lost source symbols. Depending on the codes used, the source symbols can be entirely recovered from the received encoding symbols which might be all repair symbols or some source symbols and some repair symbols. In a non-systematic encoder, the encoding symbols might include some of the source symbols, but it is possible that all of the encoding symbols are repair symbols. So as not to have to use separate terminology for systematic encoders and nonsystematic encoders, it should be understood that the term “source symbols” refers to symbols representing the data to be transmitted or provided to a destination, whereas the term “encoding symbols” refers to symbols generated by an encoder in order to improve the recoverability in the face of errors or losses, independent of whether those encoding symbols are source symbols or repair symbols. In some instances, the source symbols are preprocessed prior to presenting data to an encoder, in which case the input to the encoder might be referred to as “input symbols” to distinguish from source symbols. When a decoder decodes input symbols, typically an additional step is needed to get to the source symbols, which is typically the ultimate goal of the decoder.

One efficient code is a simple parity check code, but the robustness is often not sufficient. Another code that might be used is a rateless code such as the chain reaction codes described in U.S. Pat. No. 6,307,487, to Luby, which is assigned to the assignee hereof, and expressly incorporated by reference herein (hereinafter “Luby I”) and the multi-stage chain reaction as described in U.S. Pat. No. 7,068,729, to Shokrollahi et al., which is assigned to the assignee hereof, and expressly incorporated by reference herein (hereinafter “Shokrollahi I”).

As used herein, the term “file” refers to any data that is stored at one or more sources and is to be delivered as a unit to one or more destinations. Thus, a document, an image, and a file from a file server or computer storage device, are all examples of “files” that can be delivered. Files can be of known size (such as a one megabyte image stored on a hard disk) or can be of unknown size (such as a file taken from the output of a streaming source). Either way, the file is a sequence of source symbols, where each source symbol has a position in the file and a value.

The term “file” might also, as used herein, refer to other data to be transmitted that is not be organized or sequenced into a linear set of positions, but may instead represent data may have orderings in multiple dimensions, e.g., planar map data, or data that is organized along a time axis and along other axes according to priorities, such as video streaming data that is layered and has multiple layers that depend upon one another for presentation.

Transmission is the process of transmitting data from one or more senders to one or more recipients through a channel in order to deliver a file. A sender is also sometimes referred to as the transmitter. If one sender is connected to any number of recipients by a perfect channel, the received data can be an exact copy of the input file, as all the data will be received correctly. Here, we assume that the channel is not perfect, which is the case for most real-world channels. Of the many channel imperfections, two imperfections of interest are data erasure and data incompleteness (which can be treated as a special case of data erasure). Data erasure occurs when the channel loses or drops data. Data incompleteness occurs when a recipient does not start receiving data until some of the data has already passed it by, the recipient stops receiving data before transmission ends, the recipient chooses to only receive a portion of the transmitted data, and/or the recipient intermittently stops and starts again receiving data.

If a packet network is used, one or more symbol, or perhaps portions of symbols, are included in a packet for transmission and each packet is assumed to have been correctly received or not at all. A transmission can be “reliable”, in that the recipient and the sender will correspond with each other in the face of failures until the recipient satisfied with the result, or unreliable, in that the recipient has to deal with what is offered by the sender and thus can sometimes fail. With FEC, the transmitter encodes data, by providing additional information, or the like, to make up for information that might be lost in transit and the FEC encoding is typically done in advance of exact knowledge of the errors, attempting to prevent errors in advance.

In general, a communication channel is that which connects the sender and the recipient for data transmission. The communication channel could be a real-time channel, where the channel moves data from the sender to the recipient as the channel gets the data, or the communication channel might be a storage channel that stores some or all of the data in its transit from the sender to the recipient. An example of the latter is disk storage or other storage device. In that example, a program or device that generates data can be thought of as the sender, transmitting the data to a storage device. The recipient is the program or device that reads the data from the storage device. The mechanisms that the sender uses to get the data onto the storage device, the storage device itself and the mechanisms that the recipient uses to get the data from the storage device collectively form the channel. If there is a chance that those mechanisms or the storage device can lose data, then that would be treated as data erasure in the communication channel.

An “erasure code” is a code that maps a set of K source symbols to a larger (>K) set of encoding symbols with the property that the original source symbols can be recovered from some proper subsets of the encoding symbols. An encoder will operate to generate encoding symbols from the source symbols it is provided and will do so according to the erasure code it is provided or programmed to implement. If the erasure code is useful, the original source symbols (or in some cases, less than complete recovery but enough to meet the needs of the particular application) are recoverable from a subset of the encoding symbols that happened to be received at a receiver/decoder, if the subset is of size greater than or equal to the size of the source symbols (an “ideal” code), or at least this should be true with reasonably high probability. In practice, a “symbol” is usually a collection of bytes, possibly several hundred bytes, and all symbols (source and encoding) are the same size.

A “block erasure code” is an erasure code that maps one of a set of specific disjoint subsets of the source symbols (“blocks”) to each encoding symbol. When a set of encoding symbols is generated from one block, those encoding symbols can be used in combination with one another to recover that one block.

The “scope” of an encoding symbol is the block it is generated from and the block that the encoding symbol is used to decode, with other encoding symbols used in combination.

The “neighborhood set” of a given encoding symbol is the set of source symbols within the symbol's block that the encoding symbol directly depends on. The neighborhood set might be a very sparse subset of the scope of the encoding symbol. Many block erasure codes, including chain reaction codes (e.g., LT codes), LDPC codes, and multi-stage chain reaction codes (e.g., Raptor codes), use sparse techniques to generate encoding symbols for efficiency and other reasons. One example of a measurement of sparseness is the ratio of the number of symbols in the neighborhood set that an encoding symbol depends on to the number of symbols in the block. For example, where a block comprises 256 source symbols (k=256) and each encoding symbol is an XOR of between two and five of those 256 source symbols, the ratio would be between 2/256 and 5/256. Similarly, where K=1024 and each encoding symbol is a function of exactly three source symbols (i.e., each encoding symbol's neighborhood set has exactly three members), then the ratio is 3/1024.

For some codes, such as Raptor codes, encoding symbols are not generated directly from source symbols of the block, but instead from other intermediate symbols that are themselves generated from source symbols of the block. In any case, for Raptor codes, the neighborhood set can be much smaller than the size of the scope (which is equal to the number of source symbols in the block) of these encoding symbols. In these cases where efficient encoding and decoding is a concern and the resulting code construction is sparse, the neighborhood set of an encoding symbol can be much smaller than its scope, and different encoding symbols may have different neighborhood sets even when generated from the same scope.

Since the blocks of a block erasure code are disjoint, the encoding symbols generated from one block cannot be used to recover symbols from a different block because they contain no information about that other block. Typically, the design of codes, encoders and decoders for such disjoint block erasure codes behave a certain way due to the nature of the code. If the encoders/decoders were simply modified to allow for nondisjoint blocks, i.e., where the scope of a block might overlap another block's scope, encoding symbols generated from the overlapping blocks would not be usable to efficiently recover the source symbols from the unions of the blocks, i.e., the decoding process does not allow for efficient usage of the small neighborhood sets of the encoding symbols when used to decode overlapping blocks. As a consequence, the decoding efficiency of the block erasure codes when applied to decode overlapping blocks is much worse than the decoding efficiency of these codes when applied to what they were designed for, i.e., decoding disjoint blocks.

A “systematic code” is one in which the set of encoding symbols contains the source symbols themselves. In this context, a distinction might be made between source symbols and “repair symbols” where the latter refers to encoding symbols other than those that match the source symbols. Where a systematic code is used and all of the encoding symbols are received correctly, the extras (the repair symbols) are not needed at the receiver, but if some source symbols are lost or erased in transit, the repair symbols can be used to repair such a situation so that the decoder can recover the missing source symbols. A code is considered to be “nonsystematic” if the encoding symbols comprise the repair symbols and source symbols are not directly part of the encoding symbols.

With these definitions in mind, various embodiments will now be described.

Overview of Encoders/Decoders for Elastic Codes

In an encoder, encoding symbols are generated from source symbols, input parameters, encoding rules and possibly other considerations. In the examples of block-based encoding described herein, this set of source symbols from which an encoding symbol could depend is referred to as a “source block”, or alternatively, referred to as the “scope” of the encoding symbol. Because the encoder is block-based, a given encoding symbol depends only on source symbols within one source block (and possibly other details), or alternatively, depends only on source symbols within its scope, and does not depend on source symbols outside of its source block or scope.

Block erasure codes are useful for allowing efficient encoding, and efficient decoding. For example, once a receiver successfully recovers all of the source symbols for a given source block, the receiver can halt processing of all other received encoding symbols that encode for source symbols within that source block and instead focus on encoding symbols for other source blocks.

In a simple block erasure encoder, the source data might be divided into fixed-size, contiguous and non-overlapping source blocks, i.e., each source block has the same number of source symbols, all of the source symbols in the range of the source block are adjacent in locations in the source data and each source symbol belongs to exactly one source block. However, for certain applications, such constraints may lower performance, reduce robustness, and/or add to computational effort of encoding and/or decoding.

Elastic erasure codes are different from block erasure codes in several ways. One is that elastic erasure code encoders and decoders operate more efficiently when faced with unions of overlapping blocks. For some of the elastic erasure code methods described herein, the generated encoding symbols are sparse, i.e., their neighborhood sets are much smaller than the size of their scope, and when encoding symbols generated from a combination of scopes (blocks) that overlap are used to decode the union of the scopes, the corresponding decoder process is both efficient (leverages the sparsity of the encoding symbols in the decoding process and the number of symbol operations for decoding is substantially smaller than the number of symbol operations needed to solve a dense system of equations) and has small reception overhead (the number of encoding symbols needed to recover the union of the scopes might be equal to, or not much larger than, the size of the union of the scopes). For example, the size of the neighborhood set of each encoding symbol might be the square root of K when it is generated from a block of K source symbols, i.e., when it has scope K. Then, the number of symbol operations needed to recover the union of two overlapping blocks from encoding symbols generated from those two blocks might be much smaller than the square of K′, where the union of the two blocks comprises K′ source symbols.

With the elastic erasure coding described herein, source blocks need not be fixed in size, can possibly include nonadjacent locations, as well as allowing source blocks to overlap such that a given source symbol is “enveloped” by more than one source block.

In embodiments of an encoder described below, the data to be encoded is an ordered plurality of source symbols and the encoder determines, or obtains a determination of, demarcations of “base blocks” representing source symbols such that each source symbol is covered by one base block and a determination and demarcation of source blocks, wherein a source block envelops one or more base blocks (and the source symbols in those base blocks). Where each source block envelops exactly one base block, the result is akin to a conventional block encoder. However, there are several useful and unexpected benefits in coding when the source blocks are able to overlap each other such that some base block might be in more than one source block such that two source blocks have at least one base block in their intersection and the union of the two source blocks includes more source symbols than are in either one of the source blocks.

If the encoding is such that the portion of the source data that is represented by the union of the pair of source blocks is recoverable from a combination of a first set of encoding symbols generated from the first source block of the pair and a second set of encoding symbols generated from the second source block of the pair, it can be possible to decode using fewer received symbols that might have been required if the more simple encoding process is used. In this encoding process, the resulting encoding symbols can, in some cases, be used in combination for efficient recovery of source symbols of more than one source block.

An illustration of why this is so is provided below, but first, examples of implementations will be described. It should be understood that these implementations can be done in hardware, program code executed by a processor or computer, software running on a general purpose computer, or the like.

Elastic Code Ideal Recovery Property

For block codes, ideal recovery is the ability to recover the K source symbols of a block from any received set of K encoding symbols generated from the block. It is well-known that there are block codes with this ideal recovery property. For example, Reed-Solomon codes used as erasure codes exhibit this ideal recovery property.

A similar ideal recovery property might be defined for elastic codes. Suppose an elastic code communications system is designed such that a receiver receives some set of encoding symbols (where the channel may have caused the loss of some of the encoding symbols, so the exact set might not be specifiable at the encoder) and the receiver attempts to recover all of the original source symbols, wherein the encoding symbols are generated at the encoder from a set of overlapping scopes. The overlapping scopes are such that the received encoding symbols are generated from multiple source blocks of overlapping source symbols, wherein the scope of each received encoding symbol is one of the source blocks. In other words, encoding symbols are generated from a set of T blocks (scopes) b1, b2, . . . , bT, wherein each encoding symbol is generated from exactly one of the T blocks (scopes).

In this context, the ideal recovery property of an elastic erasure code can be described as the ability to recover the set of T blocks from a subset, E, of received encoding symbols, for any S such that 1≦S≦T, for all subsets {i1, . . . , is}, of {1, . . . , T}, if the following holds: For all s such that 1≦s≦S, for all subsets {i1′, . . . , is′} of {i1, . . . , is}, the number of symbols in E generated from any of bi′ 1 , . . . , bi′ s is at most the size of the union of bi′ 1 , . . . , bi′ s , and the number of symbols in E generated from any of bi 1 , . . . , bi s is equal to the size of the union of bi 1 , . . . , bi s . Note that E may be a subset of the received encoding symbols, i.e., some received encoding symbols might not be considered when evaluating this ideal recovery definition to see if a particular set of blocks (scopes) are recoverable.

Ideally, recovery of a set of blocks (scopes) should be computationally efficient, e.g., the number of symbol operations that the decoding process uses might be linearly proportional to the number of source symbols in the union of the recovered scopes, as opposed to quadratic, etc.

It should be noted that, while some of the descriptions herein might describe methods and processes for elastic erasure code encoding, processing, decoding, etc. that, in some cases, achieve the ideal recovery properties described above, in other cases, only a close approximation of the ideal recovery and efficiency properties of elastic codes are achieved, while still being considered to be within the definitions of elastic erasure code encoding, processing, decoding, etc.

System Overview

FIG. 1 is a block diagram of a communications system 100 that uses elastic codes.

In system 100, an elastic code block mapper (“mapper”) 110 generates mappings of base blocks to source blocks, and possibly the demarcations of base blocks as well. As shown in FIG. 1, communications system 100 includes mapper 110, storage 115 for source block mapping, an encoder array or encoder 120, storage 125 for encoding symbols, and transmitter module 130.

Mapper 110 determines, from various inputs and possibly a set of rules represented therein, which source blocks will correspond with which base blocks and stores the correspondences in storage 115. If this is a deterministic and repeatable process, the same process can run at a decoder to obtain this mapping, but if is it random or not entirely deterministic, information about how the mapping occurs can be sent to the destination to allow the decoder to determine the mapping.

As shown, a set of inputs (by no means required to be exhaustive) are used in this embodiment for controlling the operation of mapper 110. For example, in some embodiments, the mapping might depend on the values of the source symbols themselves, the number of source symbols (K), a base block structure provided as an input rather than generated entirely internal to mapper 110, receiver feedback, a data priority signal, or other inputs.

As an example, mapper 110 might be programmed to create source blocks with envelopes that depend on a particular indication of the base block boundaries provided as an input to mapper 110.

The source block mapping might also depend on receiver feedback. This might be useful in the case where receiver feedback is readily available to a transmitter and the receiver indicates successful reception of data. Thus, the receiver might signal to the transmitter that the receiver has received and recovered all source symbols up to an i-th symbol and mapper 110 might respond by altering source block envelopes to exclude fully recovered base blocks that came before the i-th symbol, which could save computational effort and/or storage at the transmitter as well as the receiver.

The source block mapping can depend on a data priority input that signals to mapper 110 varying data priority values for different source blocks or base blocks. An example usage of this is in the case where a transmitter is transmitting data and receives a signal that the data being transmitted is a lower priority than other data, in which case the coding and robustness can be increased for the higher priority data at the expense of the lower priority data. This would be useful, in applications such as map displays, where an end-user might move a “focus of interest” point as a map is loading, or in video applications where an end-user fast forwards or reverses during the transmission of a video sequence.

In any case, encoder array 120 uses the source block mapping along with the source symbol values and other parameters for encoding to generate encoding symbols that are stored in storage 125 for eventual transmission by transmitter module 130. Of course it should be understood that system 100 could be implemented entirely in software that reads source symbol values and other inputs and generates stored encoding symbols. Because the source block mapping is made available to the encoder array and encoding symbols can be independent of source symbols not in the source block associated with that encoding symbol, encoder array 120 can comprise a plurality of independently operating encoders that each operate on a different source block. It should also be understood that in some applications each encoding symbol is sent immediately or almost immediately after it is generated, and thus there might not be a need for storage 125, or an encoding symbol might be stored within storage 125 before it is transmitted for only a short duration of time.

Referring now to FIG. 2, an example of a decoder used as part of a receiver at a destination is shown. As illustrated there, a receiver 200 includes a receiver module 210, storage 220 for received encoding symbols, a decoder 230, storage 235 for decoded source symbols, and a counterpart source block mapping storage 215. Not shown is any connection needed to receive information about how to create the source block mapping, if that is needed from the transmitter.

Receiver module 210 receives the signal from the transmitter, possibly including erasures, losses and/or missing data, derives the encoding symbols from the received signal and stores the encoding symbols and storage 220.

Decoder 230 can read the encoding symbols that are available, the source block mapping from storage 215 to determine which symbols can be decoded from the encoding symbols based on the mappings, the available encoding symbols and the previously decoded symbols in storage 235. The results of decoder 230 can be stored in storage 235.

It should be understood that storage 220 for received encoded symbols and storage 235 for decoded source symbols might be implemented by a common memory element, i.e., wherein decoder 230 saves the results of decoding in the same storage area as the received encoding symbols used to decode. It should also be understood from this disclosure that encoding symbols and decoded source symbols may be stored in volatile storage, such as random-access memory (RAM) or cache, especially in cases where there is a short delay between when encoding symbols first arrive and when the decoded data is to be used by other applications. In other applications, the symbols are stored in different types of memory.

FIG. 3 illustrates in more detail an encoder 300, which might be the encoder shown in FIG. 1, or one encoder unit in an encoder array. In any case, as illustrated, encoder 300 has a symbol buffer 305 in which values of source symbols are stored. In the illustration, all K source symbols are storable at once, but it should be understood that the encoder can work equally as well with a symbol buffer that has less than all of the source symbols. For example, a given operation to generate an encoding symbol might be carried out with symbol buffer only containing one source block's worth of source symbols, or even less than an entire source block's worth of source symbols.

A symbol selector 310 selects from one to K of the source symbol positions in symbol buffer 305 and an operator 320 operates on the operands corresponding to the source symbols and thereby generates an encoding symbol. In a specific example, symbol selector 310 uses a sparse matrix to select symbols from the source block or scope of the encoding symbols being generated and operator 320 operates on the selected symbols by performing a bit-wise exclusive or (XOR) operation on the symbols to arrive at the encoding symbols. Other operations besides XOR are possible.

As used herein, the source symbols that are operands for a particular encoding symbol are referred to as that encoding symbol's “neighbors” and the set of all encoding symbols that depend on a given source symbol are referred to as that source symbol's neighborhood.

When the operation is an XOR, a source symbol that is a neighbor of an encoding symbol can be recovered from that encoding symbol if all the other neighbors source symbols of that encoding symbol are available, simply by XORing the encoding symbol and the other neighbors. This may make it possible to decode other source symbols. Other operations might have like functionality.

With the neighbor relationships known, a graph of source symbols and encoding symbols would exist to represent the encoding relationships.

Details of Elastic Codes

Elastic codes have many advantages over either block codes or convolutional codes or network codes, and easily allow for what is coded to change based on feedback received during encoding. Block codes are limited due to the requirement that they code over an entire block of data, even though it may be advantageous to code over different parts of the data as the encoding proceeds, based on known error-conditions of the channel and/or feedback, taking into consideration that in many applications it is useful to recover the data in prefix order before all of the data can be recovered due to timing constraints, e.g., when streaming data.

Convolutional codes provide some protection to a stream of data by adding repair symbols to the stream in a predetermined patterned way, e.g., adding repair symbols to the stream at a predetermined rate based on a predetermined pattern. Convolutional codes do not allow for arbitrary source block structures, nor do they provide the flexibility to generate varying amounts of encoding symbols from different portions of the source data, and they are limited in many other ways as well, including recovery properties and the efficiency of encoding and decoding.

Network codes provide protection to data that is transmitted through a variety of intermediate receivers, and each such intermediate receiver then encodes and transmits additional encoding data based on what it received. Network codes do not provide the flexibility to determine source block structures, nor are there known efficient encoding and decoding procedures that are better than brute force, and network codes are limited in many other ways as well.

Elastic codes provide a suitable level of data protection while at the same time allowing for real-time streaming experience, i.e., introducing as little latency in the process as possible given the current error conditions due to the coding introduced to protect against error-conditions.

As explained, an elastic code is a code in which each encoding symbol may be dependent on an arbitrary subset of the source symbols. One type of the general elastic code is an elastic chord code in which the source symbols are arranged in a sequence and each encoding symbol is generated from a set of consecutive source symbols. Elastic chord codes are explained in more detail below.

Other embodiments of elastic codes are elastic codes that are also linear codes, i.e., in which each encoding symbol is a linear sum of the source symbols on which it depends and a GF(q) linear code is a linear code in which the coefficients of the source symbols in the construction of any encoding symbol are members of the finite field GF(q).

Encoders and decoders and communications systems that use the elastic codes as described herein provide a good balance of minimizing latency and bandwidth overhead.

Elastic Code Uses for Multi-Priority Coding

Elastic codes are also useful in communications systems that need to deliver objects that comprise multiple parts for those parts may have different priorities of delivery, where the priorities are determined either statically or dynamically.

An example of static priority would be data that is partitioned into different parts to be delivered in a priority that depends on the parts, wherein different parts may be logically related or dependent on one another, in either time or some other causality dimension. In this case, the protocol might have no feedback from receiver to sender, i.e., be open-loop.

An example of dynamic priority would be a protocol that is delivering two-dimensional map information to an end user dynamically in parts as the end user focus on different parts of the map changes dynamically and unpredictably. In this case, the priority of the different parts of the map to be delivered changes based on unknown a-priori priorities that are only known based on feedback during the course of the protocol, e.g., in reaction to changing network conditions, receiver input or interest, or other inputs. For example, an end user may change their interest in terms of which next portion of the map to view based on information in their current map view and their personal inclinations and/or objectives. The map data may be partitioned into quadrants, and within each quadrant to different levels of refinement, and thus there might be a base block for each level of each quadrant, and source blocks might comprise unions of one or more base blocks, e.g., some source blocks might comprise unions of the base blocks associated with different levels of refinement within one quadrant, whereas other source blocks might comprise unions of base blocks associated with adjacent quadrants of one refinement level. This is an example of a closed-loop protocol.

Encoders Using Elastic Erasure Coding

Encoders described herein use a novel coding that allows encoding over arbitrary subsets of data. For example, one repair symbol can encode over one set of data symbols while a second repair symbol can encode over a second set of data symbols, in such a way that the two repair symbols can recover from the loss of two source symbols in the intersections of their scopes, and each repair symbol can recover from the loss of one data symbol from the data symbols that is in their scope but not in the scope of the other repair symbol. One advantage of elastic codes is that they can provide an elastic trade-off between recovery capabilities and end-to-end latency. Another advantage of such codes is that they can be used to protect data of different priorities in such a way that the protection provided solely for the highest priority data can be combined with the data provided for the entire data to recover the entire data, even in the case when the repair provided for the highest priority data is not alone sufficient for recovery of the highest priority data.

These codes are useful in complete protocol designs in cases where there is no feedback and in cases where there is feedback within the protocol. In the case where there is feedback in the protocol, the codes can be dynamically changed based on the feedback to provide the best combination of provided protection and added latency due to the coding.

Block codes can be considered a degenerate case of using elastic codes, by having single source scopes—each source symbol belongs in only one source block. With elastic codes, source scope determination can be completely flexible, source symbols can belong to multiple source scopes, source scopes can be determined on the fly, in other than a pre-defined regular pattern, determined by underlying structure of source data, determined by transport conditions or other factors.

FIG. 4 illustrates an example, wherein the lower row of boxes represents source symbols and the bracing above the symbols indicates the envelope of the source blocks. In this example, there are three source blocks and thus there would be three encoded blocks, one that encodes for each one of the source blocks. In this example, if source blocks are formed from base blocks, there could be five base blocks with the base blocks demarcations indicated with arrows.

In general, encoders and decoders that use elastic codes would operate where each of the source symbols is within one base block but can be in more than one source block, or source scope, with some of the source blocks being overlapping and at least in some cases not entirely subsets of other source blocks, i.e., there are at least two source blocks that have some source symbols in common but also each have some source symbols present in one of the source blocks but not in the other. The source block is the unit from which repair symbols are generated, i.e., the scope of the repair symbols, such that repair symbols for one source block can be independent of source symbols not in that source block, thereby allowing the decoding of source symbols of a source block using encoded, received, and/or repair symbols of that source block without requiring a decoder to have access to encoded, received, or repair symbols of another source block.

The pattern of scopes of source blocks can be arbitrary, and/or can depend on the needs or requests of a destination decoder. In some implementations, source scope can be determined on-the-fly, determined by underlying structure of source data, determined by transport conditions, and/or determined by other factors. The number of repair symbols that can be generated from a given source block can be the same for each source block, or can vary. The number of repair symbols generated from a given source block may be fixed based on a code rate or may be independent of the source block, as in the case of chain reaction codes.

In the case of traditional block codes or chain reaction codes, repair symbols that are used by the decoder in combination with each other to recover source symbols are typically generated from a single source block, whereas with the elastic codes described herein, repair symbols can be generated from arbitrary parts of the source data, and from overlapping parts of the source data, and the mapping of source symbols to source blocks can be flexible.

Selected Design Considerations

Efficient encoding and decoding is primary concern in the design of elastic codes. For example, ideal efficiency might be found in an elastic code that can decode using a number of symbol operations that is linear in the number of recovered source symbols, and thus any decoder that uses substantially fewer symbol operations for recovery than brute force methods is preferable, where typically a brute force method requires a number of symbol operations that is quadratic in the number of recovered source symbols.

Decoding with minimal reception overhead is also a goal, where “reception overhead” can be represented as the number of extra encoding symbols, beyond what is needed by a decoder, that are needed to achieve the previously described ideal recovery properties. Furthermore, guaranteed recovery, or high probability recovery, or very high likelihood recovery, or in general high reliability recovery, are preferable. In other words, in some applications, the goal need not be complete recovery.

Elastic codes are useful in a number of environments. For example with layered coding, a first set of repair symbols is provided to protect a block of higher priority data, while a second set of repair symbols protects the combination of the higher priority data block and a block of lower priority data, requiring fewer symbols at decoding and if the higher priority data block was encoded separately and the lower priority data block was encoded separately. Some known codes provide for layered coding, but often at the cost of failing to achieve efficient decoding of unions of overlapping source blocks and/or failing to achieve high reliability recovery.

The elastic window-based codes described below can achieve efficient and high reliability decoding of unions of overlapping source blocks at the same time and can also do so in the case of layered coding.

Combination with Network Coding

In another environment, network coding is used, where an origin node sends encoding of source data to intermediate nodes that may experience different loss patterns and intermediate nodes send encoding data generated from the portion of the encoding data that is received to destination nodes. The destination nodes can then recover the original source data by decoding the received encoding data received from multiple intermediate nodes. Elastic codes can be used within a network coding protocol, wherein the resulting solution provides efficient and high reliability recovery of the original source data.

Simple Construction of Elastic Chord Codes

For the purposes of explanation, assume an encoder generates a set of repair symbols as follows, which provides a simple construction of elastic chord codes. This simple construction can be extended to provide elastic codes that are not necessarily elastic chord codes, in which case the identification of a repair symbol and its neighborhood set or scope is an extension of the identification described here. Generate an mn matrix, A, with elements in GF(256). Denote the element in the i-th row and j-th column by Aij and the source symbols by Sj for j=0, 1, 2, . . . . Then, for any tuple (e, l, i), where e, l and i are integers, e≧l>0 and 0≦i<m and a repair symbol Re,l,i has a value as set out in Equation 1.

R e , l , i = j = e - l + 1 j = e A ij S jmodn ( Eqn . 1 )

Note that for Re,l,i to be well-defined, a notion of multiplication of a symbol by an element of GF(256) and a notion of summation of symbols should be specified. In examples, herein, elements of GF(256) are represented as octets and each symbol, which can be a sequence of octets, is thought of as a sequence of elements of GF(256). Multiplication of a symbol by a field element entails multiplication of each element of the symbol by the same field element. Summation of symbols is simply the symbol formed from the concatenation of the sums of the corresponding field elements in the symbols to be summed.

The set of source symbols that appear in Equation 1 for a given repair symbol is known as the “scope” of the repair symbol, whereas the set of repair symbols that have a given source symbol appear in Equation 1 for each of those repair symbols is referred to as the “neighborhood” of the given source symbol. Thus, in this construction, the neighborhood set of a repair symbol is the same as the scope of the repair symbol.

The encoding symbols of the code then comprise the source symbols plus repair symbols, as defined herein, i.e., the constructed code is systematic.

Consider two alternative constructions for the matrix A, corresponding to two different elastic codes. For a “Random Chord Code”, the elements of A are chosen pseudo-randomly from the nonzero elements of GF(256). It should be understood herein throughout, unless otherwise indicated, where something is described as being chosen randomly, it should be assumed that pseudo-random selection is included in that description and, more generally, that random operations can be performed pseudo-randomly. For a “Cauchy Chord Code”, the elements of A are defined as shown in Equation 2, where k=255−m, and g(x) is the finite field element whose octet representation is x.
A ij=(g(j mod k)⊕g(255−i))−1  (Eqn. 2)
Decoding Symbols from an Encoding Using a Simple Construction of Elastic Chord Codes

As well as encoding symbols themselves, the decoder has access to identifying information for each symbol, which can just be an index, i.e., for a source symbol, Sj, the identifying information is the index, j. For a repair symbol, Re,l,i, the identifying information is the triple (e, l, i). Of course, the decoder also has access to the matrix A.

For each received repair symbol, a decoder determines the identifying information and calculates a value for that repair symbol from Equation 1 using source symbol values if known and the zero symbol if the source symbol value is unknown. When the value so calculated is added to the received repair symbol, assuming the repair symbol was received correctly, the result is a sum over the remaining unknown source symbols in the scope or neighborhood of the repair symbol.

For simplicity, this description has a decoder programmed to attempt to recover all unknown source symbols that are in the scope of at least one received repair symbol. Upon reading this disclosure, it should be apparent how to modify the decoder to recover less than all, or all with a high probability but less than certainty, or a combination thereof.

In this example, let t be the number of unknown source symbols that are in the union of the scopes of received repair symbols and let j0, j1, . . . , jt-1 be the indices of these unknown source symbols. Let u be the number of received repair symbols and denote the received repair symbols (arbitrarily) as R0, . . . , Ru-1.

Construct the ut matrix E with entries Epq, where Epq is the coefficient of source symbol Sj q in Equation 1 for repair symbol Rp, or zero if Sj q does not appear in the equation. Then, if S=(Sj 0 , . . . , Sj t−1 )T is a vector of the missing source symbols and R=(R0, . . . , Ru-1)T is a vector of the received repair symbols after applying step 1, the expression in Equation 3 will be satisfied.
R=ES  (Eqn. 3)

If E does not have rank u, then there exists a row of E that can be removed without changing the rank of E. Remove this, decrement u by one and renumber the remaining repair symbols so that Equation 3 still holds. Repeat this step until E has rank u.

If u=t, then complete decoding is possible, E is square, of full rank and therefore invertible. Since E is invertible, S can be found from E−1R, and decoding is complete. If u<t, then complete decoding is not possible without reception of additional source and/or repair symbols of this subset of the source symbols or having other information about the source symbols from some other avenue.

If u<t, then let E′ be a uu sub-matrix of E of full rank. With a suitable column permutation, E can be written as (E′|U), where U is a u(t−u) matrix. Multiplying both sides of Equation 3 by E′−1, the expression in Equation 4 can be obtained, which provides a solution for the source symbols corresponding to rows of E−1R where E′−1U is zero.
E′ −1 R=(I|E′ −1 U)S  (Eqn. 4)

Equation 4 allows simpler recovery of the remaining source symbols if further repair and/or source symbols are received.

Recovery of other portions of the source symbols might be possible even when recovery of all unknown source symbols that are in the scope of at least one received repair symbol is not possible. For example, it may be the case that, although some unknown source symbols are in the scope of at least one received repair symbol, there are not enough repair symbols to recover the unknown source symbols, or that some of the equations between the repair symbols and unknown source symbols are linearly dependent. In these cases, it may be possible to at least recover a smaller subset of the source symbols, using only those repair symbols with scopes that are within the smaller subset of source symbols.

Stream Based Decoder Using Simple Construction of Elastic Chord Codes

In a “stream” mode of operation, the source symbols form a stream and repair symbols are generated over a suffix of the source symbols at the time the repair is generated. This stream based protocol uses the simple construction of the elastic chord codes described above.

At the decoder, source and repair symbols arrive one by one, possibly with some reordering and as soon as a source or repair symbol arrives, the decoder can identify whether any lost source symbol becomes decodable, then decode and deliver this source symbol to the decoder's output.

To achieve this, the decoder maintains a matrix (I|E′−1U) and updates this each time a new source or repair symbol is received according to the procedures below.

Let D denote the “decoding matrix”, (I|E′−1U). Let Dij denote the element at position (i,j), D*j denote the j-th column of D and Di* denote the i-th row of D.

In the procedures described below, the decoder performs various operations on the decoding matrix. The equivalent operations are performed on the repair symbols to effect decoding. These could be performed concurrently with the matrix operations, but in some implementations, these operations are delayed until actual source symbols are recovered in the RecoverSymbols procedure described below.

Upon receipt of a source symbol, if the source symbol is one of the missing source symbols, Sj q , then the decoder removes the corresponding column of D. If the removed column was one of the first u columns, then the decoder identifies the repair symbol associated with the row that has a nonzero element in the removed column. The decoder then repeats the procedure described below for receipt of this repair symbol. If the removed column was not one of the first u columns, then the decoder performs the RecoverSymbols procedure described below.

Upon receipt of a repair symbol, first the decoder adds a new column to D for each source symbol that is currently unknown, within the scope of the new repair symbol and not already associated with a column of D. Next, the decoder adds a new row, Du*, to D for the received repair symbol, populating this row with the coefficients from Equation 1.

For i from 0 to u−1 inclusive, the decoder replaces Du* with (Du*−MuiDi*). This step results in the first u elements of Du* being eliminated (i.e., reduced to zero). If Du* is nonzero after this elimination step, then the decoder performs column exchanges (if necessary) so that Duu is nonzero and replaces Du* with (Duu −1Du*).

For i from u−1 to 0 inclusive, the decoder replaces Di* with (Di*−DiuDu*). This step results in the elements of column u being eliminated (i.e., reduced to zero) except for row u.

The matrix is now once again in the form (I|E′−1U) and the decoder can set u:=u+1.

To perform the RecoverSymbols procedure, the decoder considers each row of E′−1U that is zero, or for all rows of D if E′−1U is empty. The source symbol whose column is nonzero in that row of D can be recovered. Recovery is achieved by performing the stored sequence of operations upon the repair symbols. Specifically, whenever the decoder replaces row Di* with (Di*−αDj*), it also replaces the corresponding repair symbol Ri with (Ri−αRi) and whenever row Di* is replaced with (αDi*), it replaces repair symbol Ri with αRi.

Note that the order in which the operations are performed is important and are the same as the order in which the matrix operations were performed.

Once the operations have been performed, then for each row of E′−1U that is zero, the corresponding repair symbol now has a value equal to that of the source symbol whose column is nonzero in that row of D and the symbol has therefore been recovered. This row and column can then be removed from D.

In some implementations, symbol operations are only performed when it has been identified that at least one symbol can be recovered. Symbol operations are performed for all rows of D but might not result in recovery of all missing symbols. The decoder therefore tracks which repair symbols have been “processed” and which have not and takes care to keep the processed symbols up-to-date as further matrix operations are performed.

A property of elastic codes, in this “stream” mode, is that dependencies may stretch indefinitely into the past and so the decoding matrix D may grow arbitrarily large. Practically, the implementation should set a limit on the size of D. In practical applications, there is often a “deadline” for the delivery of any given source symbol—i.e., a time after which the symbol is of no use to the protocol layer above or after which the layer above is told to proceed anyway without the lost symbol.

The maximum size of D may be set based on this constraint. However, it may be advantageous for the elastic code decoder to retain information that may be useful to recover a given source symbol even if that symbol will never be delivered to the application. This is because the alternative is to discard all repair symbols with a dependency on the source symbol in question and it may be the case that some of those repair symbols could be used to recover different source symbols whose deadline has not expired.

An alternative limit on the size of D is related to the total amount of information stored in the elastic code decoder. In some implementations, received source symbols are buffered in a circular buffer and symbols that have been delivered are retained, as these may be needed to interpret subsequently received repair symbols (e.g., calculating values in Equation 1 above). When a source symbol is finally discarded (due to the buffer being full) it is necessary to discard (or process) any (unprocessed) repair symbols whose scope includes that symbol. Given this fact, and a source buffer size, perhaps the matrix D should be sized to accommodate the largest number of repair symbols expected to be received whose scopes are all within the source buffer.

An alternative implementation would be to construct the matrix D only when there was a possibility of successful decoding according to the ideal recovery property described above.

Computational Complexity

The computational complexity of the code described above is dominated by the symbol operations.

Addition of symbols can be the bitwise exclusive OR of the symbols. This can be achieved efficiently on some processors by use of wide registers (e.g., the SSE registers on CPUs following an x86 architecture), which can perform an XOR operation over 64 or 128 bits of data at a time. However, multiplication of symbols by a finite field element often must be performed byte-by-byte, as processors generally do not provide native instructions for finite field operations and therefore lookup tables must be used, meaning that each byte multiplication requires several processor instructions, including access to memory other than the data being processed.

At the encoder, Equation 1 above is used to calculate each repair symbol. This involves l symbol multiplications and l−1 symbol additions, where l is the number of source symbols in the scope of the repair symbol. If each source symbol is protected by exactly r repair symbols, then the total complexity is O(rk) symbol operations, where k is the number of source symbols. Alternatively, if each repair symbol has a scope or neighborhood set of l source symbols, then the computational complexity per generated repair symbol is O(l) symbol operations. As used herein, the expression O( ) should be understood to be the conventional “on the order of” function.

At the decoder, there are two components to the complexity: the elimination of received source symbols and the recovery of lost source symbols. The first component is equivalent to the encoding operation, i.e., O(rk) symbol operations. The second component corresponds to the symbol operations resulting from the inversion of the uu matrix E, where u is the number of lost source symbols, and thus has complexity O(u2) symbol operations.

For low loss rates, u is small and therefore, if all repair symbols are used at the decoder, encoding and decoding complexity will be similar. However, since the major component of the complexity scales with the number of repair symbols, if not all repair symbols are used, then complexity should decrease.

As noted above, in an implementation, processing of repair symbols is delayed until it is known that data can be recovered. This minimizes the symbol operations and so the computational requirements of the code. However, it results in bursts of decoding activity.

An alternative implementation can smooth out the computational load by performing the elimination operations for received source symbols (using Equation 1) as symbols arrive. This results in performing elimination operations for all the repair symbols, even if they are not all used, which results in higher (but more stable) computational complexity. For this to be possible, the decoder must have information in advance about which repair symbols will be generated, which may not be possible in all applications.

Decoding Probability

Ideally, every repair symbol is either clearly redundant because all the source symbols in its scope are already recovered or received before it is received, or is useful for recovering a lost source symbol. How frequently this is true depends on the construction of the code.

Deviation from this ideal might be detected in the decoder logic when a new received repair symbol results in a zero row being added to D after the elimination steps. Such a symbol carries no new information to the decoder and thus is discarded to avoid unnecessary processing.

In the case of the random GF(256) code implementation, this may be to be the case for roughly 1 repair symbol in 256, based on the fact that when a new random row is added to a uu+1 matrix over GF(256) of full rank, the probability that the resulting uu matrix does not have full rank is 1/256.

In the case of the Cauchy code implementation, when used as a block code and where the total number of source and repair symbols is less than 256, the failure probability is zero. Such a code is equivalent to a Reed-Solomon code.

Block Mode Results

In tests of elastic chord codes used as a block code (i.e., generating a number of repair symbols all with scope equal to the full set of k source symbols), for fixed block size (k=256) and repair amount (r=8), encode speed and decode speed are about the same for varying block sizes above about 200 bytes, but below that, speed drops. This is likely because below 200 byte symbols (or some other threshold depending on conditions), the overhead of the logic required to determine the symbol operations is substantial compared to the symbol operations themselves, but for larger symbol sizes the symbol operations themselves are dominant.

In other tests, encoding and decoding speed as a function of the repair overhead (r/k) for fixed block and symbol size showed that that encoding and decoding complexity is proportional to the number of repair symbols (and so speed is proportional to 1/r).

Stream Mode Results

When the loss rate is much less than the overhead, the average latency is low but it increases quickly as the loss rate approaches the code overhead. This is what one would expect because when the loss rate is much less than the overhead, then most losses can be recovered using a single repair symbol. As the loss rate increases, we more often encounter cases where multiple losses occur within the scope of a single repair symbol and this requires more repair symbols to be used.

Another fine-tuning that might occur is to consider the effect of varying the span of the repair symbols (the span is how many source symbols are in the scope or neighborhood set of the repair symbol), which was 256 in the examples above. Reducing the span, for a fixed overhead, reduces the number of repair symbols that protect each source symbol and so one would expect this to increase the residual error rate. However, reducing the span also reduces the computational complexity at both encoder and decoder.

Window-based Code that is a Fountain Block Code

In many encoders and decoders, the amount of computing power and time allotted to encoding and decoding is limited. For example, where the decoder is in a battery-powered handheld device, decoding should be efficient and not require excessive computing power. One measure of the computing power needed for encoding and decoding operations is the number of symbol operations (adding two symbols, multiplying, XORing, copying, etc.) that are needed to decode a particular set of symbols. A code should be designed with this in mind. While the exact number of operations might not be known in advance, since it might vary based on which encoding symbols are received and how many encoding symbols are received, it is often possible to determine an average case or a worst case and configure designs accordingly.

This section describes a new type of fountain block code, herein called a “window-based code,” that is the basis of some of the elastic codes described further below that exhibit some aspects of efficient encoding and decoding. The window-based code as first described is a non-systematic code, but as described further below, there are methods for transforming this into a systematic code that will be apparent upon reading this disclosure. In this case, the scope of each encoding symbol is the entire block of K source symbols, but the neighborhood set of each encoding symbol is much sparser, consisting of B<<K neighbors, and the neighborhood sets of different encoding symbols are typically quite different.

Consider a block of K source symbols. The encoder works as follows. First, the encoder pads (logically or actually) the block with B zero symbols on each side to form an extended block of K+2B symbols, X0, X1, . . . , XK+2B−1, i.e., the first B symbols and the last B symbols are zero symbols, and the middle K symbols are the source symbols. To generate an encoding symbol, the encoder randomly selects a start position, t, between 1 and K+B−1 and chooses values α0, . . . , αB−1 randomly or pseudo-randomly from a suitable finite field (e.g., GF(2) or GF(256)). The encoding symbol value, ESV, is then calculated by the encoder using the formula of Equation 5, in which case the neighborhood set of the generated encoding symbol is selected among the symbols in positions t through t+B−1 in the extended block.
ESV=Σ j=0 B−1αj X t+j  (Eqn. 5)

The decoder, upon receiving at least K encoding symbols, uses a to-and-fro sweep across the positions of the source symbols in the extended block to decode. The first sweep is from the source symbol in the first position to the source symbol in the last position of the block, matching that source symbol, s, with an encoding symbol, e, that can recover it, and eliminating dependencies on s of encoding symbols that can be used to recover source symbols in later positions, and adjusting the contribution of s to e to be simply s. The second sweep is from the source symbol in the last position to the source symbol in the first position of the block, eliminating dependencies on that source symbol s of encoding symbols used to recover source symbols in earlier positions. After a successful to-and-fro sweep, the recovered value of each source symbol is the value of the encoding symbol to which it is matched.

For the first sweep process, the decoder obtains the set, E, of all received encoding symbols. For each source symbol, s, in position i=B, . . . , B+K−1 within the extended block, the decoder selects the encoding symbol e that has the earliest neighbor end position among all encoding symbols in E that have s in their neighbor set and then matches e to s and deletes e from E. This selection is amongst those encoding symbols e for which the contribution of s to e in the current set of linear equations is non-zero, i.e., s contributes βs to e, where β≠0. If there is no encoding symbol e to which the contribution of s is non-zero, then decoding fails, as s cannot be decoded. Once source symbol s is matched with an encoding symbol e, encoding symbol e is removed from the set E, Gaussian elimination is used to eliminate the contribution of s to all encoding symbols in E, and the contribution of s to e is adjusted to be simply s by multiplying e by the inverse of the coefficient of the contribution of s to e.

The second sweep process of the decoder works as follows. For each source symbol, s, in source position i=K−1, . . . , 0, Gaussian elimination is used to eliminate the contribution of s to all encoding symbols in E matched to source symbols in positions previous to i.

The decoding succeeds in fully recovering all the source symbols if and only if the system of linear equations defined by the received encoding symbols is of rank K, i.e., if the received encoding symbols have rank K, then the above decoding process is guaranteed to recover the K source symbols of the block.

The number of symbol operations per generated encoding symbol is B.

The reach of an encoding symbol is defined to be the set of positions within the extended block between the first position that is a neighbor of the encoding symbol and the last position that is a neighbor of the encoding symbol. In the above construction, the size of the reach of each encoding symbols is B. The number of decoding symbol operations is bounded by the sum of sizes of the reaches of the encoding symbols used for decoding. This is because, by the way the matching process described above is designed, an encoding symbol reach is never extended during the decoding process and each decoding symbol operation decreases the sum of the sizes of the encoding symbol reaches by one. This implies that the number of symbol operations for decoding the K source symbols is O(KB).

There is a trade-off between the computational complexity of the window-based code and its recovery properties. It can be shown by a simple analysis that if B=O(K1/2) and if the finite field size is chosen to be large enough, e.g., O(K), then all K source symbols of the block can be recovered with high probability from K received encoding symbols, and the failure probability decreases rapidly as a function of each additionally received encoding symbol. The recovery properties of the window-based code are similar to those of a random GF[2] code or random GF[256] code when GF[2] or GF[256] are used as the finite field, respectively, and B=O(K1/2).

A similar analysis can be use to show that if B=O(ln(K/δ)/ε) then all K source symbols of the block can be recovered with probability at least 1−δ after K(1+ε) encoding symbols have been received.

There are many variations of the window-based codes described herein, as one skilled in the art will recognize. As one example, instead of creating an extended block of K+2B symbols, instead one can generate encoding symbols directly from the K source symbols, in which case t is chosen randomly between 0 and K−1 for each encoding symbol, and then the encoding symbol value is computed as shown in Equation 6. One way to decode for this modified window-based block code is to use a decoding procedure similar to that described above, except at the beginning a consecutive set of B of the K source symbols are “inactivated”, the decoding proceeds as described previously assuming that these B inactivated source symbol values are known, a BB system of equations between encoding symbols and the B inactivated source symbols is formed and solved, and then based on this and the results of the to-and-fro sweep, the remaining K−B source symbols are solved. Details of how this can work are described in Shokrollahi-Inactivation.
ESV=Σ j=0 B−1αj X (t+j)mod K  (Eqn. 6)
Systematic Window-Based Block Code

The window-based codes described above are non-systematic codes. Systematic window-based codes can be constructed from these non-systematic window-based codes, wherein the efficiency and recovery properties of the so-constructed systematic codes are very similar to those of the non-systematic code from which they are constructed.

In a typical implementation, the K source symbols are placed at the positions of the first K encoding symbols generated by the non-systematic code, decoded to obtain an extended block, and then repair symbols are generated for the systematic code from the decoded extended block. Details of how this can work are described in Shokrollahi-Systematic. A simple and preferred such systematic code construction for this window-based block code is described below.

For the non-systematic window-based code described above that is a fountain block code, a preferred way to generate the first K encoding symbols in order to construct a systematic code is the following. Instead of choosing the start position t between 1 and K+B−1 for the first K encoding symbols, instead do the following. Let B′=B/2 (assume without loss of generality that B is even). Choose t=B′, B′+1, . . . , B′+K−1 for the first K encoding symbols. For the generation of the first K encoding symbols, the generation is exactly as described above, with the possible exception, if it is not already the case, that the coefficient αB′ is chosen to be a non-zero element of the finite field (making this coefficient non-zero ensures that the decoding process can recover the source symbol corresponding to this coefficient from this encoding symbol). By the way that these encoding symbols are constructed, it is always possible to recover the K source symbols of the block from these first K encoding symbols.

The systematic code encoding construction is the following. Place the values of the K source symbols at the positions of the first K encoding symbols generated according to the process described in the previous paragraph of the non-systematic window-based code, use the to-and-fro decoding process of the non-systematic window-based code to decode the K source symbols of the extended block, and then generate any additional repair symbols using the non-systematic window-based code applied to the extended block that contains the decoded source symbols that result from the to-and-fro decoding process.

The mapping of source symbols to encoding symbols should use a random permutation of K to ensure that losses of bursts of consecutive source symbols (and other patterns of loss) do not affect the recoverability of the extended block from any portion of encoding symbols, i.e., any pattern and mix of reception of source and repair symbols.

The systematic decoding process is the mirror image of the systematic encoding process. Received encoding symbols are used to recover the extended block using the to-and-fro decoding process of the non-systematic window-based code, and then the non-systematic window-based encoder is applied to the extended block to encode any missing source symbols, i.e., any of the first K encoding symbols that are missing.

One advantage of this approach to systematic encoding and decoding, wherein decoding occurs at the encoder and encoding occurs at the decoder, is that the systematic symbols and the repair symbols can be created using a process that is consistent across both. In fact, the portion of the encoder that generates the encoding symbols need not even be aware that K of the encoding symbols will happen to exactly match the original K source symbols.

Window-Based Code that is a Fountain Elastic Code

The window-based code fountain block code can be used as the basis for constructing a fountain elastic code that is both efficient and has good recovery properties. To simplify the description of the construction, we describe the construction when there are multiple base blocks X1, . . . , XL of equal size, i.e., each of the L basic blocks comprise K source symbols. Those skilled in the art will recognize that these constructions and methods can be extended to the case when the basic blocks are not all the same size.

As described previously, a source block may comprise the union of any non-empty subset of the L base blocks. For example, one source block may comprise the first base block and a second source block may comprise the first and second base blocks and a third source block may comprise the second and third base blocks. In some cases, some or all of the base blocks have different sizes and some or all of the source blocks have different sizes.

The encoder works as follows. First, for each base block Xi, the encoder pads (logically or actually) the block with B zero symbols on each side to form an extended block of K+2B symbols X0 i, X1 i, . . . , XK+2B−1 i, the first B symbols and the last B symbols are zero symbols, and the middle K symbols are the source symbols of base block Xi.

The encoder generates an encoding symbol for source block S as follows, where S comprises L′ base blocks, and without loss of generality assume that these are the base blocks X1, . . . , XL′. The encoder randomly selects a start position, t, between 1 and K+B−1 and for all i=1, . . . , L′, chooses values α0 i, . . . , αB−1 i randomly from a suitable finite field (e.g., GF(2) or GF(256)). For each i=1, . . . , L′, the encoder generates an encoding symbol value based on the same starting position t, i.e., as shown in Equation 7.
ESV ij=0 B−1αj i X t+j i  (Eqn. 7)

Then, the generated encoding symbol value ESV for the source block is simply the symbol finite field sum over i=1, . . . , L′ of ESVi, i.e., as shown in Equation 8.

ESV = i = 1 , , L ESV i ( Eqn . 8 )

Suppose the decoder is used to decode a subset of the base blocks, and without loss of generality assume that these are the base blocks X1, . . . , XL′. To recover the source symbols in these L′ base blocks, the decoder can use any received encoding symbol generated from source blocks that are comprised of a union of a subset of X1, . . . , XL′. To facilitate efficient decoding, the decoder arranges a decoding matrix, wherein the rows of the matrix correspond to received encoding symbols that can be used for decoding, and wherein the columns of the matrix correspond to the extended blocks for base blocks X1, . . . , XL′ arranged in the interleaved order:
X0 1, X0 2, . . . , X0 L′, X1 1, X1 2, . . . , X1 L′, . . . , XK+2B−1, XK+2B−1 2, . . . , XK+2B−1 L′

Similar to the previously described to-and-fro decoder for a fountain block code, the decoder uses a to-and-fro sweep across the column positions in the above described matrix to decode. The first sweep is from the smallest column position to the largest column position of the matrix, matching the source symbol s that corresponds to that column position with an encoding symbol e that can recover it, and eliminating dependencies on s of encoding symbols that can be used to recover source symbols that correspond to later column positions, and adjusting the contribution of s to e to be simply s. The second sweep is from the largest column position to the smallest column position of the matrix from the source symbol in the last position to the source symbol in the first position of the block, eliminating dependencies on the source symbol s that corresponds to that column position of encoding symbols used to recover source symbols in earlier positions. After a successful to-and-fro sweep, the recovered value of each source symbol is the value of the encoding symbol to which it is matched.

For the first sweep process, the decoder obtains the set, E, of all received encoding symbols that can be useful for decoding base blocks X1, . . . , XL′. For each position i=L′B, . . . , L′(B+K)−1 that corresponds to source symbol s of one of the L′ basic blocks, the decoder selects the encoding symbol e that has the earliest neighbor end position among all encoding symbols in E that have s in their neighbor set and then matches e to s and deletes e from E. This selection is amongst those encoding symbols e for which the contribution of s to e in the current set of linear equations is non-zero, i.e., s contributes βs to e, where β≠0. If there is no encoding symbol e to which the contribution of s is non-zero then decoding fails, as s cannot be decoded. Once source symbol s is matched with an encoding symbol e, encoding symbol e is removed from the set E, Gaussian elimination is used to eliminate the contribution of s to all encoding symbols in E, and the contribution of s to e is adjusted to be simply s by multiplying e by the inverse of the coefficient of the contribution of s to e.

The second sweep process of the decoder works as follows. For each position i=L′(B+K)−1, . . . , L′B that corresponds to source symbol s of one of the L′ basic blocks, Gaussian elimination is used to eliminate the contribution of s to all encoding symbols in E matched to source symbols corresponding to positions previous to i.

The decoding succeeds in fully recovering all the source symbols if and only if the system of linear equations defined by the received encoding symbols is of rank L′K, i.e., if the received encoding symbols have rank L′K, then the above decoding process is guaranteed to recover the L′K source symbols of the L′ basic blocks.

The number of symbol operations per generated encoding symbol is BV, where V is the number of basic blocks enveloped by the source block from which the encoding symbol is generated.

The reach of an encoding symbol is defined to be the set of column positions between the smallest column position that corresponds to a neighbor source symbol and the largest column position that corresponds to a neighbor source symbol in the decoding matrix. By the properties of the encoding process and the decoding matrix, the size of the reach of an encoding symbol is at most BL′ in the decoding process described above. The number of decoding symbol operations is at most the sum of the sizes of the reaches of the encoding symbols, as by the properties of the matching process described above, the reach of encoding symbols are never extended beyond their original reach by decoding symbol operations and each decoding symbol operation decreases the sum of the sizes of the encoding symbol reaches by one. This implies that, and that the number of symbol operations for decoding the N=KL′ source symbols in L′ basic blocks is O(NBL′).

There is a trade-off between the computational complexity of the window-based code and its recovery properties. It can be shown by a simple analysis that if B=O(ln(L)K1/2) and if the finite field size is chosen to be large enough, e.g., O(LK), then all L′K source symbols of the L′ basic blocks can be recovered with high probability if the recovery conditions of an ideal recovery elastic code described previously are satisfied by the received encoding symbols for the L′ basic blocks, and the failure probability decreases rapidly as a function of each additionally received encoding symbol. The recovery properties of the window-based code are similar to those of a random GF[2] code or random GF[256] code when GF[2] or GF[256] are used as the finite field, respectively, and B=O(ln(L)K1/2).

A similar analysis can be used to show that if B=O(ln(LK/δ)/ε) then all L′K source symbols of the L′ basic blocks can be recovered with probability at least 1−δ under the following conditions. Let T be the number of source blocks from which the received encoding symbols that are useful for decoding the L′ basic blocks are generated. Then, the number of received encoding symbols generated from the T source blocks should be at least L′K(1+ε), and for all S≦T, the number of encoding symbols generated from any set of S source blocks should be at most the number of source symbols in the union of those S source blocks.

The window-based codes described above are non-systematic elastic codes. Systematic window-based fountain elastic codes can be constructed from these non-systematic window-based codes, wherein the efficiency and recovery properties of the so-constructed systematic codes are very similar to those of the non-systematic code from which they are constructed, similar to the systematic construction described above for the window-based codes that are fountain block codes. Details of how this might work are described in Shokrollahi-Systematic.

There are many variations of the window-based codes described herein, as one skilled in the art will recognize. As one example, instead of creating an extended block of K+2B symbols for each basic block, instead one can generate encoding symbols directly from the K source symbols of each basic block that is part of the source block from which the encoding symbols is generated, in which case t is chosen randomly between 0 and K−1 for each encoding symbol, and then the encoding symbol value is computed similar to that shown in Equation 6 for each such basic block.

One way to decode for this modified window-based block code is to use a decoding procedure similar to that described above, except at the beginning a consecutive set of L′B of the L′K source symbols are “inactivated”, the decoding proceeds as described previously assuming that these L′B inactivated source symbol values are known, a L′BL′B system of equations between encoding symbols and the L′B inactivated source symbols is formed and solved, and then based on this and the results of the to-and-fro sweep, the remaining L′(K−B) source symbols are solved. Details of how this can work are described in Shokrollahi-Inactivation.

There are many other variations of the window-based code above. For example, it is possible to relax the condition that each basic block comprises the same number of source symbols. For example, during the encoding process, the value of B used for encoding each basic block can be proportional to the number of source symbols in that basic block. For example, suppose a first basic block comprises K source symbols and a second basic block comprises K′ source symbols, and let μ=K/K′ be the ratio of the sizes of the blocks. Then, the value B used for the first basic block and the corresponding value B′ used for the second basic block can satisfy: B/B′=μ. In this variation, the start position within the two basic blocks for computing the contribution of the basic blocks to an encoding symbol generated from a source block that envelopes both basic blocks might differ, for example the encoding process can choose a value φ uniformly between 0 and 1 and then use the start position t=φ(K+B−1) for the first basic block and use the start position t′=φ(K′+B′−1) for the second basic block (where these values are rounded up to the nearest integer position). In this variation, when forming the decoding matrix at the decoder comprising the interleaved symbols from each of the basic blocks being decoded, the interleaving can be done in such a way that the frequency of positions corresponding to the first basic block to the frequency of positions corresponding to the second basic block is in the ratio μ, e.g., if the first basic block is twice the size of the second basic block then twice as many column positions correspond to the first basic block as correspond to the second basic block, and this condition is true (modulo rounding errors) for any consecutive set of column positions within the decoding matrix.

There are many other variations as well, as one skilled in the art will recognize. For example, a sparse matrix representation of the decoding matrix can be used at the decoder instead of having to store and process the full decoding matrix. This can substantially reduce the storage and time complexity of decoding.

Other variations are possible as well. For example, the encoding may comprise a mixture of two types of encoding symbols: a majority of a first type of encoding symbols generated as described above and a minority of a second type of encoding symbols generated sparsely at random. For example the fraction of the first type of encoding symbols could be 1−K−1/3 and the reach of each first type encoding symbol could be B=O(K1/3), and the fraction of the second type of encoding symbols could be K−1/3 and the number of neighbors of each second type encoding symbol could be K2/3. One advantage of such a mixture of two types of encoding symbols is that the value of B used for the first type to ensure successful decoding can be substantially smaller, e.g., B=O(K1/3) when two types are used as opposed to B=O(K1/2) when only one type is used.

The decoding process is modified so that in a first step the to-and-fro decoding process described above is applied to the first type of encoding symbols, using inactivation decoding to inactivate source symbols whenever decoding is stuck to allow decoding to continue. Then, in a second step the inactivated source symbol values are recovered using the second type of encoding symbols, and then in a third step these solved encoding symbol values together with the results of the first step of the to-and-fro decoding are used to solve for the remaining source symbol values. The advantage of this modification is that the encoding and decoding complexity is substantially improved without degrading the recovery properties. Further variations, using more than two types of encoding symbols, are also possible to further improve the encoding and decoding complexity without degrading the recovery properties.

Ideal Recovery Elastic Codes

This section describes elastic codes that achieve the ideal recovery elastic code properties described previously. This construction applies to the case when the source blocks satisfy the following conditions: the source symbols can be arranged into an order such that the source symbols in each source block are consecutive, and so that, for any first source block and for any second source block, the source symbols that are in the first source block but not in the second source block are either all previous to the second source block or all subsequent to the second source block, i.e., there is no first and second source blocks with some symbols of the first source block preceding the second source block and some symbols of the first source block following the second source block. For brevity, herein such codes are referred to as a No-Subset Chord Elastic code, or “NSCE code.” NSCE codes include prefix elastic codes.

It should be understood that the “construction” herein may involve mathematical concepts that can be considered in the abstract, but that such constructions are applied to a useful purpose and/or for transforming data, electrical signals or articles. For example, the construction might be performed by an encoder that seeks to encode symbols of data for transmission to a receiver/decoder that in turn will decode the encodings. Thus, inventions described herein, even where the description focuses on the mathematics, can be implemented in encoders, decoders, combinations of encoders and decoders, processes that encoder and/or decode, and can also be implemented by program code stored on computer-readable media, for use with hardware and/or software that would cause the program code to be executed and/or interpreted.

In an example construction of an NSCE code, a finite field with nc(n) field elements is used, where c(n)=O(nC), where C is the number of source blocks. An outline of the construction follows, and implementation should be apparent to one of ordinary skill in the art upon reading this outline. This construction can be optimized to further reduce the size of the needed finite field, at least somewhat, in some cases.

In the outline, n is the number of source symbols to be encoded and decoded, C is the number of source blocks, also called chords, used in the encoding process, c(n) is some predetermined value that is on the order of nC. Since a chord is a subset (proper or not) of the n source symbols that are used in generating repair symbols and a “block” is a set of symbols generated from within the same domain, there is a one-to-one correspondence between the chords used and the blocks used. The use of these elements will now be described with reference to an encoder or a decoder, but it should be understood that similar steps might be performed by both, even if not explicitly stated.

An encoder will manage a variable, j, that can range from 1 to C and indicates a current block/chord being processed. By some logic or calculation, the encoder determines, for each block j, the number of source symbols, kj, and the number of encoding symbols, nj, associated with block j. The encoder can then construct a kjnj Cauchy matrix, Mj, for block j. The size of the field needed for the base finite field to represent the Cauchy matrices is thus the maximum of kj+nj over all j. Let q be the number of elements in this base field.

The encoder works over a larger field, F, with qD elements, where D is on the order of qC. Let ω be an element of F that is of degree D. The encoder uses (at least logically) powers of ω to alter the matrices to be used to compute the encoding symbols. For block 1 of the C blocks, the matrix M1 is left unmodified. For block 2, the row of M2 that corresponds to i-th source symbol is multiplied by ωi. For block j, the row of Mj that corresponds to i-th source symbol is multiplied by ωiq(j), where q(j)=qj−2.

Let the modified matrices be M′1, . . . , M′C. These are the matrices used to generate the encoding symbols for the C blocks. A key property of these matrices flows from an observation explained below.

Suppose a receiver has received some mix of encoding symbols generated from the various blocks. That receiver might want to determine whether the determinant of the matrix M corresponding to the source symbols and the received encoding symbols is nonzero.

Consider the bipartite graph between the received encoding symbols and the source symbols, with adjacencies defined naturally, i.e., there is an edge between an encoding symbol and a source symbol if the source symbol is part of the block from which the encoding symbol is generated. If there is a matching within this graph where all of the source symbols are matched, then the source symbols should be decodable from the received encoding symbols, i.e., the determinant of M should not be zero. Then, classify each matching by a “signature” of how the source symbols are matched to the blocks of encoding symbols, e.g., a signature of (1, 1, 3, 2, 3, 1, 2, 3) indicates that, in this matching, the first source symbol is matched to an encoding symbol in block 1, the second source symbol is matched to an encoding symbol in block 1, the third source symbol is matched to an encoding symbol in block 3, the fourth source symbol is matched to an encoding symbol in block 2, etc. Then, the matchings can be partitioned according to their signatures, and the determinant of M can be viewed as the sum of determinants of matrices defined by these signatures, where each such signature determinant corresponds to a Cauchy matrix and is thus not zero. However, the signature determinants could zero each other out.

By constructing the modified matrices M′1, . . . , M′C, a result is that there is a signature that uniquely has the largest power of ω as a coefficient of the determinant corresponding to that signature, and this implies that the determinant of M is not zero since the determinant of this unique signature cannot be zeroed out by any other determinant. This is where the chord structure of the blocks is important.

Let the first block correspond to the chord that starts (and ends) first within the source symbols, and in general, let block j correspond to the chord that is the j-th chord to start (and finish) within the source blocks. Since there are no subset chords, if any one block starts before second one, it also has to end before the second one, otherwise the second one is a subset.

Then, the decoder handles a matching wherein all of the encoding symbols for the first block are matched to a prefix of the source symbols, wherein all of the encoding symbols for the second block are matched to a next prefix of the source symbols (excluding the source symbols matched to the first block), etc. In particular, this matching will have the signature of e1 1's followed by e2 2's, followed by e3 3's, etc., where ei is the number of encoding symbols that are to be used to decode the source symbols that were generated from block i. This matching has a signature that uniquely has the largest power of ω as a coefficient (similar to the argument used in the Theorem 1 for the two-chord case), i.e., any other signature that corresponds to a valid matching between the source and received encoding symbols will have a smaller power of ω as a coefficient. Thus, the determinant has to be nonzero.

One disadvantage with chord elastic codes occurs where subsets exist, i.e., where there is one chord contained within another chord. In such cases, a decoder cannot be guaranteed to always find a matching where the encoding symbols for each block are used greedily, i.e., use all for block 1 on the first source symbols, followed by block 2, etc., at least according to the original ordering of the source symbols.

In some cases, the source symbols can be re-ordered to obtain the non-contained chord structure. For example, if the set of chords according to an original ordering of the source symbols were such that each subsequent chord contains all of the previous chords, then the source symbols can be re-ordered so that the structure is that of a prefix code, i.e., re-order the source symbols from the inside to the out, so that the first source symbols are those inside all of the chords, followed by those source symbols inside all but the smallest chord, followed by those source symbols inside all but the smallest two chords, etc. With this re-ordering, the above constructions can be applied to obtain elastic codes with ideal recovery properties.

Examples of Usage of Elastic Codes

In one example, the encoder/decoder are designed to deal with expected conditions, such as a round-trip time (RTT) for packets of 400 ms, a delivery rate of 1 Mbps (bits/second), and a symbol size of 128 bytes. Thus, the sender sends approximately 1000 symbols per second (1000 symbols/sec128 bytes/symbol8 bits/byte=1.024 Mbps). Assume moderate loss conditions of some light loss (e.g., at most 5%) and sometimes heavier loss (e.g., up to 50%).

In one approach, a repair symbol is inserted after each G source symbols, and where the maximum latency can be as little as G symbols to recover from loss, X=1/G is the fraction of repair symbols that is allowed to be sent that may not recover any source symbols. G can change based on current loss conditions, RTT and/or bandwidth.

Consider the example in FIG. 5, where the elastic code is a prefix code and G=4. The source symbols are shown sequentially, and the repair symbols are shown with bracketed labels representing the source block that the repair symbol applies to.

If all losses are consecutive starting at the beginning, and one symbol is lost, then the introduced latency is at most G, whereas if two symbols are lost, then the introduced latency is at most 2G, and if i symbols are lost, the introduced latency is at most iG. Thus, the amount of loss affects introduced latency linearly.

Thus, if the allowable redundant overhead is limited to 5%, say, then G=20, i.e., one repair symbol is sent for each 20 source symbols. In the above example, one symbol is sent per 1 ms, so that would mean 20 ms between each repair symbol and the recovery time would be 40 ms for two lost symbols, 60 ms for three lost symbols, etc. Note that using just ARQ in these conditions, recovery time is at least 400 ms, the RTT.

In that example, a repair symbol's block is the set of all prior sent symbols. Where simple report back from the receiver are allowed, the blocks can be modified to exclude earlier source symbols that have been received or are no longer needed. An example is shown in FIG. 6, which is a variation of what is shown in FIG. 5.

In this example, assume that the encoder receives from the sender a SRSI indicator of the smallest Relevant Source Index. The SRSI can increase each time all prior source symbols are received or are no longer needed. Then, the encoder does not need to have any repair symbols depend on source symbols that have indices lower than the SRSI, which saves on computation. Typically, the SRSI is the index of the source symbol immediately following the largest prefix of already recovered source symbols. The sender then calculates scope of a repair symbol from the largest SRSI received from the receiver to the last sent index of a source symbol. This leads to exactly the same recovery properties as the no-feedback version, but lessens complexity/memory requirements at the sender and the receiver. In the example of FIG. 6, SRSI=5.

With the feedback, prefix elastic codes can be used more efficiently and feedback reduces complexity/memory requirements. When a sender gets feedback indicative of loss, it can adjust the scope of repair symbols accordingly. Thus, to combine forward error correction and reactive error correction, additional optimizations are possible. For example, the forward error correction (FEC) can be tuned so that the allowable redundant overhead is high enough to proactively recover most losses, but not too high as to introduce too much overhead, while reactive correction is for the more rare losses. Since most losses are quickly recovered using FEC, most losses are recovered without an RTT latency penalty. While reactive correction has an RTT latency penalty, its use is rarer.

Variations

Source block mapping indicates which blocks of source symbols are used for determining values for a set of encoding symbols (which can be encoding symbols in general or more specifically repair symbols). In particular, a source block mapping might be stored in memory and indicate the extents of a plurality of base blocks and indicate which of those base blocks are “within the scope” of which source blocks. In some cases, at least one base block is in more than one source block. In many implementations, the operation of an encoder or decoder can be independent of the source block mapping, thus allowing for arbitrary source block mapping. Thus, while predefined regular patterns could be used, that is not required and in fact, source block scopes might be determined from underlying structure of source data, by transport conditions or by other factors.

In some embodiments, an encoder and decoder can apply error-correcting elastic coding rather than just elastic erasure coding. In some embodiments, layered coding is used, wherein one set of repair symbols protects a block of higher priority data and a second set of repair symbols protects the combination of the block of higher priority data and a block of lower priority data.

In some communication systems, network coding is combined with elastic codes, wherein an origin node sends encoding of source data to intermediate nodes and intermediate nodes send encoding data generated from the portion of the encoding data that the intermediate node received—the intermediate node might not get all of the source data, either by design or due to channel errors. Destination nodes then recover the original source data by decoding the received encoding data from intermediate nodes, and then decodes this again to recover the source data.

In some communication systems that use elastic codes, various applications can be supported, such as progressive downloading for file delivery/streaming when prefix of a file/stream needs to be sent before it is all available, for example. Such systems might also be used for PLP replacement or for object transport.

Those of ordinary skill in the art would further appreciate, after reading this disclosure, that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the exemplary embodiments of the invention.

The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), flash memory, Read Only Memory (ROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-Ray™ disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

The previous description of the disclosed exemplary embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these exemplary embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US390972128 Feb 197430 Sep 1975SignatronSignal processing system
US436533827 Jun 198021 Dec 1982Harris CorporationTechnique for high rate digital transmission over a dynamic dispersive channel
US458911226 Jan 198413 May 1986International Business Machines CorporationSystem for multiple error detection with single and double bit error correction
US490131918 Mar 198813 Feb 1990General Electric CompanyTransmission system with adaptive interleaving
US513659228 Jun 19894 Aug 1992Digital Equipment CorporationError detection and correction system for long burst errors
US51535914 Jul 19896 Oct 1992British Telecommunications Public Limited CompanyMethod and apparatus for encoding, decoding and transmitting data in compressed form
US533132016 Nov 199219 Jul 1994International Business Machines CorporationCoding method and apparatus using quaternary codes
US537153215 May 19926 Dec 1994Bell Communications Research, Inc.Communications architecture and method for distributing information services
US537253226 Jan 199313 Dec 1994Robertson, Jr.; George W.Swivel head cap connector
US53792979 Apr 19923 Jan 1995Network Equipment Technologies, Inc.Concurrent multi-channel segmentation and reassembly processors for asynchronous transfer mode
US542103123 Dec 199330 May 1995Delta Beta Pty. Ltd.Program transmission optimisation
US54250509 Nov 199313 Jun 1995Massachusetts Institute Of TechnologyTelevision transmission system using spread spectrum and orthogonal frequency-division multiplex
US543278724 Mar 199411 Jul 1995Loral Aerospace CorporationPacket data transmission system with adaptive data recovery method
US545582319 Oct 19923 Oct 1995Radio Satellite CorporationIntegrated communications terminal
US546531818 Jun 19937 Nov 1995Kurzweil Applied Intelligence, Inc.Method for generating a speech recognition model for a non-vocabulary utterance
US551750826 Jan 199414 May 1996Sony CorporationMethod and apparatus for detection and error correction of packetized digital data
US552402516 Nov 19924 Jun 1996At&T Corp.Coding for digital transmission
US556620817 Mar 199415 Oct 1996Philips Electronics North America Corp.Encoder buffer having an effective size which varies automatically with the channel bit-rate
US556861429 Jul 199422 Oct 1996International Business Machines CorporationData streaming between peer subsystems of a computer system
US558378412 May 199410 Dec 1996Fraunhofer-Gesellschaft Zur Forderung Der Angewandten Forschung E.V.Frequency analysis method
US560873810 Nov 19944 Mar 1997Nec CorporationPacket transmission method and apparatus
US561754121 Dec 19941 Apr 1997International Computer Science InstituteSystem for packetizing data encoded corresponding to priority levels where reconstructed data corresponds to fractionalized priority level and received fractionalized packets
US56423658 Jun 199424 Jun 1997Mitsubishi Denki Kabushiki KaishaTransmitter for encoding error correction codes and a receiver for decoding error correction codes on a transmission frame
US565961428 Nov 199419 Aug 1997Bailey, Iii; John E.Method and system for creating and storing a backup copy of file data stored on a computer
US56994739 Oct 199616 Dec 1997Samsung Electronics Co., Ltd.Method for recording and reproducing intercoded data using two levels of error correction
US570158222 Mar 199523 Dec 1997Delta Beta Pty. Ltd.Method and apparatus for efficient transmissions of programs
US575133612 Oct 199512 May 1998International Business Machines CorporationPermutation based pyramid block transmission scheme for broadcasting in video-on-demand storage systems
US575456311 Sep 199519 May 1998Ecc Technologies, Inc.Byte-parallel system for implementing reed-solomon error-correcting codes
US575741523 May 199526 May 1998Sony CorporationOn-demand data transmission by dividing input data into blocks and each block into sub-blocks such that the sub-blocks are re-arranged for storage to data storage means
US58023946 Jun 19941 Sep 1998Starlight Networks, Inc.Method for accessing one or more streams in a video storage system using multiple queues and maintaining continuity thereof
US580582526 Jul 19958 Sep 1998Intel CorporationMethod for semi-reliable, unidirectional broadcast information services
US58351657 Jun 199510 Nov 1998Lsi Logic CorporationReduction of false locking code words in concatenated decoders
US584463613 May 19971 Dec 1998Hughes Electronics CorporationMethod and apparatus for receiving and recording digital packet data
US587041212 Dec 19979 Feb 19993Com CorporationForward error correction system for packet based real time media
US59037756 Jun 199611 May 1999International Business Machines CorporationMethod for the sequential transmission of compressed video information at varying data rates
US591785211 Jun 199729 Jun 1999L-3 Communications CorporationData scrambling system and method and communications system incorporating same
US592620522 Jan 199720 Jul 1999Imedia CorporationMethod and apparatus for encoding and formatting data representing a video program to provide multiple overlapping presentations of the video program
US593305615 Jul 19973 Aug 1999Exar CorporationSingle pole current mode common-mode feedback circuit
US593665931 Jan 199710 Aug 1999Telcordia Technologies, Inc.Method for video delivery using pyramid broadcasting
US59369495 Sep 199610 Aug 1999Netro CorporationWireless ATM metropolitan area network
US595353714 Jun 199414 Sep 1999Altera CorporationMethod and apparatus for reducing the number of programmable architecture elements required for implementing a look-up table in a programmable logic device
US59700982 Oct 199719 Oct 1999Globespan Technologies, Inc.Multilevel encoder
US598338317 Jan 19979 Nov 1999Qualcom IncorporatedMethod and apparatus for transmitting and receiving concatenated code data
US599305628 Jul 199730 Nov 1999Stevens Institute Of TechnologyHigh integrity transport for time critical multimedia networking applications
US600547715 Apr 199821 Dec 1999Abb Research Ltd.Method and apparatus for information transmission via power supply lines
US60115903 Jan 19974 Jan 2000Ncr CorporationMethod of transmitting compressed information to minimize buffer space
US601215917 Jan 19974 Jan 2000Kencast, Inc.Method and system for error-free data transfer
US601470614 Mar 199711 Jan 2000Microsoft CorporationMethods and apparatus for implementing control functions in a streamed video display system
US601835924 Apr 199825 Jan 2000Massachusetts Institute Of TechnologySystem and method for multicast video-on-demand delivery system
US604100125 Feb 199921 Mar 2000Lexar Media, Inc.Method of increasing data reliability of a flash memory device without compromising compatibility
US60444853 Jan 199728 Mar 2000Ericsson Inc.Transmitter method and transmission system using adaptive coding based on channel characteristics
US606182028 Dec 19959 May 2000Kabushiki Kaisha ToshibaScheme for error control on ATM adaptation layer in ATM networks
US60732506 Nov 19976 Jun 2000Luby; Michael G.Loss resilient decoding technique
US60790412 Aug 199620 Jun 2000Sanyo Electric Co., Ltd.Digital modulation circuit and digital demodulation circuit
US607904229 Apr 199620 Jun 2000The Trustees Of The Stevens Institute Of TechnologyHigh integrity transport for time critical multimedia networking applications
US60819079 Jun 199727 Jun 2000Microsoft CorporationData delivery system and method for delivering data and redundant information over a unidirectional network
US60819096 Nov 199727 Jun 2000Digital Equipment CorporationIrregularly graphed encoding technique
US60819186 Nov 199727 Jun 2000Spielman; Daniel A.Loss resilient code with cascading series of redundant layers
US60883301 Oct 199711 Jul 2000Bruck; JoshuaReliable array of distributed computing nodes
US609732020 Jan 19981 Aug 2000Silicon Systems, Inc.Encoder/decoder system with suppressed error propagation
US613459618 Sep 199717 Oct 2000Microsoft CorporationContinuous media file server system and method for scheduling network resources to play multiple files having different data transmission rates
US61410533 Jan 199731 Oct 2000Saukkonen; Jukka I.Method of optimizing bandwidth for transmitting compressed video data streams
US614178715 Jan 199931 Oct 2000Sanyo Electric Co., Ltd.Digital modulation and demodulation
US614178813 Oct 199831 Oct 2000Lucent Technologies Inc.Method and apparatus for forward error correction in packet networks
US615445226 May 199928 Nov 2000Xm Satellite Radio Inc.Method and apparatus for continuous cross-channel interleaving
US61638706 Nov 199719 Dec 2000Compaq Computer CorporationMessage encoding with irregular graphing
US616654425 Nov 199826 Dec 2000General Electric CompanyMR imaging system with interactive image contrast control
US617594415 Jul 199716 Jan 2001Lucent Technologies Inc.Methods and apparatus for packetizing data for transmission through an erasure broadcast channel
US617853614 Aug 199723 Jan 2001International Business Machines CorporationCoding scheme for file backup and systems based thereon
US61852657 Apr 19986 Feb 2001Worldspace Management Corp.System for time division multiplexing broadcast channels with R-1/2 or R-3/4 convolutional coding for satellite transmission via on-board baseband processing payload or transparent payload
US61957776 Nov 199727 Feb 2001Compaq Computer CorporationLoss resilient code with double heavy tailed series of redundant layers
US62233245 Jan 199924 Apr 2001Agere Systems Guardian Corp.Multiple program unequal error protection for digital audio broadcasting and other applications
US62262596 Mar 19981 May 2001Canon Kabushiki KaishaDevice and method for transmitting information device and method for processing information
US622630119 Feb 19981 May 2001Nokia Mobile Phones LtdMethod and apparatus for segmentation and assembly of data frames for retransmission in a telecommunications system
US62298244 Nov 19998 May 2001Xm Satellite Radio Inc.Method and apparatus for concatenated convolutional endcoding and interleaving
US624384617 Apr 19985 Jun 20013Com CorporationForward error correction system for packet based data and real time media, using cross-wise parity calculation
US627265827 Oct 19987 Aug 2001Kencast, Inc.Method and system for reliable broadcasting of data files and streams
US627871623 Mar 199821 Aug 2001University Of MassachusettsMulticast with proactive forward error correction
US629846218 Jun 19982 Oct 2001Samsung Electronics Co., Ltd.Data transmission method for dual diversity systems
US63074875 Feb 199923 Oct 2001Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US63142893 Dec 19986 Nov 2001Fraunhofer-Gesellschaft zur Frderung der angewandten Forschung e.V.Apparatus and method for transmitting information and apparatus and method for receiving information
US632052017 Sep 199920 Nov 2001Digital FountainInformation additive group code generator and decoder for communications systems
US63321631 Sep 199918 Dec 2001Accenture, LlpMethod for providing communication services over a computer network system
US633392611 Aug 199825 Dec 2001Nortel Networks LimitedMultiple user CDMA basestation modem
US63734068 Jan 200116 Apr 2002Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US639306528 Aug 199821 May 2002Canon Kabushiki KaishaCoding and decoding methods and devices and equipment using them
US641122318 Oct 200025 Jun 2002Digital Fountain, Inc.Generating high weight encoding symbols using a basis
US641532615 Sep 19982 Jul 2002Microsoft CorporationTimeline correlation between multiple timeline-altered media streams
US642098218 Dec 200116 Jul 2002Mosaid Technologies, Inc.Multi-stage lookup for translating between signals of different bit lengths
US642138710 Aug 200016 Jul 2002North Carolina State UniversityMethods and systems for forward error correction based loss recovery for interactive video transmission
US643023330 Aug 19996 Aug 2002Hughes Electronics CorporationSingle-LNB satellite data receiver
US64457171 May 19983 Sep 2002Niwot Networks, Inc.System for recovering lost information in a data stream
US64598111 Apr 19991 Oct 2002Sarnoff CorporationBursty data transmission of compressed video data
US646669825 Mar 199915 Oct 2002The United States Of America As Represented By The Secretary Of The NavyEfficient embedded image and video compression system using lifted wavelets
US647301026 Jun 200029 Oct 2002Marvell International, Ltd.Method and apparatus for determining error correction code failure rate for iterative decoding algorithms
US648680322 Sep 200026 Nov 2002Digital Fountain, Inc.On demand encoding with a window
US648769221 Dec 199926 Nov 2002Lsi Logic CorporationReed-Solomon decoder
US64969807 Dec 199817 Dec 2002Intel CorporationMethod of providing replay on demand for streaming digital multimedia
US649747927 Apr 200124 Dec 2002Hewlett-Packard CompanyHigher organic inks with good reliability and drytime
US651017724 Mar 200021 Jan 2003Microsoft CorporationSystem and method for layered video coding enhancement
US652314711 Nov 199918 Feb 2003Ibiquity Digital CorporationMethod and apparatus for forward error correction coding for an AM in-band on-channel digital audio broadcasting system
US65359206 Apr 199918 Mar 2003Microsoft CorporationAnalyzing, indexing and seeking of streaming information
US657759930 Jun 199910 Jun 2003Sun Microsystems, Inc.Small-scale reliable multicasting
US658454314 Nov 200224 Jun 2003Micron Technology, Inc.Reconfigurable memory with selectable error correction storage
US66092236 Apr 200019 Aug 2003Kencast, Inc.Method for packet-level fec encoding, in which on a source packet-by-source packet basis, the error correction contributions of a source packet to a plurality of wildcard packets are computed, and the source packet is transmitted thereafter
US661436614 Feb 20022 Sep 2003Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US661845113 Feb 19999 Sep 2003Altocom IncEfficient reduced state maximum likelihood sequence estimator
US66311721 May 20007 Oct 2003Lucent Technologies Inc.Efficient list decoding of Reed-Solomon codes for message recovery in the presence of high noise levels
US663385610 Oct 200114 Oct 2003Flarion Technologies, Inc.Methods and apparatus for decoding LDPC codes
US664136625 Jan 20024 Nov 2003Thorsten NordhoffWind power generating system with an obstruction lighting or night marking device
US66433329 Jul 19994 Nov 2003Lsi Logic CorporationMethod and apparatus for multi-level coding of digital signals
US667786418 Apr 200213 Jan 2004Telefonaktiebolaget L.M. EricssonMethod for multicast over wireless networks
US66788552 Dec 199913 Jan 2004Microsoft CorporationSelecting K in a data transmission carousel using (N,K) forward error correction
US66944762 Jun 200017 Feb 2004Vitesse Semiconductor CorporationReed-solomon encoder and decoder
US670437013 Apr 19999 Mar 2004Nortel Networks LimitedInterleaving methodology and apparatus for CDMA
US67323258 Nov 20004 May 2004Digeo, Inc.Error-correction with limited working storage
US674215425 May 200025 May 2004Ciena CorporationForward error correction codes for digital optical network optimization
US67484412 Dec 19998 Jun 2004Microsoft CorporationData carousel receiving and caching
US67517726 Jul 200015 Jun 2004Samsung Electronics Co., Ltd.Rate matching device and method for a data communication system
US676586629 Feb 200020 Jul 2004Mosaid Technologies, Inc.Link aggregation
US680420218 Jan 200012 Oct 2004Lg Information And Communications, Ltd.Radio protocol for mobile communication system and method
US68104994 Jun 200126 Oct 2004Vitesse Semiconductor CorporationProduct code based forward error correction system
US682022113 Apr 200116 Nov 2004Hewlett-Packard Development Company, L.P.System and method for detecting process and network failures in a distributed system
US68311728 Nov 199914 Dec 2004Farmila-Thea Farmaceutici S.P.A.Cross-linked hyaluronic acids and medical uses thereof
US684980323 Feb 20011 Feb 2005Arlington Industries, Inc.Electrical connector
US685073621 Dec 20001 Feb 2005Tropian, Inc.Method and apparatus for reception quality indication in wireless communication
US685626310 Jun 200315 Feb 2005Digital Fountain, Inc.Systems and processes for decoding chain reaction codes through inactivation
US686808316 Feb 200115 Mar 2005Hewlett-Packard Development Company, L.P.Method and system for packet communication employing path diversity
US687662316 Feb 19995 Apr 2005Agere Systems Inc.Tuning scheme for code division multiplex broadcasting system
US68826186 Sep 200019 Apr 2005Sony CorporationTransmitting apparatus, receiving apparatus, communication system, transmission method, reception method, and communication method
US689554711 Jul 200117 May 2005International Business Machines CorporationMethod and apparatus for low density parity check encoding of data
US69093831 Oct 200321 Jun 2005Digital Fountain, Inc.Systematic encoding and decoding of chain reaction codes
US692860319 Jul 20019 Aug 2005Adaptix, Inc.System and method for interference mitigation using adaptive forward error correction in a wireless RF data transmission system
US693761817 Nov 200030 Aug 2005Sony CorporationSeparating device and method and signal receiving device and method
US695687519 Jun 200218 Oct 2005Atlinks Usa, Inc.Technique for communicating variable bit rate data over a constant bit rate link
US696563630 Oct 200015 Nov 20052Wire, Inc.System and method for block error correction in packet-based digital communications
US698545921 Aug 200210 Jan 2006Qualcomm IncorporatedEarly transmission and playout of packets in wireless communication systems
US699569230 Sep 20047 Feb 2006Matsushita Electric Industrial Co., Ltd.Data converter and method thereof
US701005216 Apr 20017 Mar 2006The Ohio UniversityApparatus and method of CTCM encoding and decoding for a digital communication system
US70307857 Jan 200518 Apr 2006Digital Fountain, Inc.Systems and processes for decoding a chain reaction code through inactivation
US703125722 Sep 200018 Apr 2006Lucent Technologies Inc.Radio link protocol (RLP)/point-to-point protocol (PPP) design that passes corrupted data and error location information among layers in a wireless data transmission protocol
US705753419 Jun 20036 Jun 2006Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US706868115 Aug 200327 Jun 2006Samsung Electronics Co., Ltd.Apparatus and method for exchanging variable-length data according to radio link protocol in mobile communication system
US706872921 Dec 200127 Jun 2006Digital Fountain, Inc.Multi-stage code generator and decoder for communication systems
US707297122 Feb 20014 Jul 2006Digital Foundation, Inc.Scheduling of multiple files for serving on a server
US70731916 Apr 20014 Jul 2006Sun Microsystems, IncStreaming a single media track to multiple clients
US71001882 Jun 200329 Aug 2006Enounce, Inc.Method and apparatus for controlling time-scale modification during multi-media broadcasts
US711041218 Sep 200119 Sep 2006Sbc Technology Resources, Inc.Method and system to transport high-quality video signals
US713966014 Jul 200421 Nov 2006General Motors CorporationSystem and method for changing motor vehicle personalization settings
US71399606 Oct 200421 Nov 2006Digital Fountain, Inc.Error-correcting multi-stage code generator and decoder for communication systems having single transmitters or multiple transmitters
US714343327 Dec 200028 Nov 2006Infovalve Computing Inc.Video distribution system using dynamic segmenting of video data files
US715175422 Sep 200019 Dec 2006Lucent Technologies Inc.Complete user datagram protocol (CUDP) for wireless multimedia packet networks using improved packet level forward error correction (FEC) coding
US715495116 Mar 200426 Dec 2006Microsoft CorporationMotion video signal encoder and encoding method
US71643706 Oct 200516 Jan 2007Analog Devices, Inc.System and method for decoding data compressed in accordance with dictionary-based compression schemes
US716488224 Dec 200216 Jan 2007Poltorak Alexander IApparatus and method for facilitating a purchase using information provided on a media playing device
US716803017 Oct 200323 Jan 2007Telefonaktiebolaget Lm Ericsson (Publ)Turbo code decoder with parity information update
US721928915 Mar 200515 May 2007Tandberg Data CorporationMultiply redundant raid system and XOR-efficient method and apparatus for implementing the same
US723140431 Jan 200312 Jun 2007Nokia CorporationDatacast file transmission with meta-data retention
US723326413 Sep 200519 Jun 2007Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US724023623 Mar 20043 Jul 2007Archivas, Inc.Fixed content distributed data storage using permutation ring encoding
US724035823 Jan 20013 Jul 2007Digital Fountain, Inc.Methods and apparatus for scheduling, serving, receiving media-on demand for clients, servers arranged according to constraints on resources
US724328510 Jul 200310 Jul 2007Digital Fountain, Inc.Systems and methods for broadcasting information additive codes
US724929114 Feb 200324 Jul 2007Digital Fountain, Inc.System and method for reliably communicating the content of a live data stream
US725475414 Jul 20037 Aug 2007International Business Machines CorporationRaid 3+3
US725776412 Aug 200414 Aug 2007Broadcom CorporationFEC (Forward Error Correction) decoder with dynamic parameters
US726568815 Feb 20064 Sep 2007Digital Fountain, Inc.Systems and processes for decoding a chain reaction code through inactivation
US729322229 Jan 20046 Nov 2007Digital Fountain, Inc.Systems and processes for fast encoding of hamming codes
US729557320 Aug 200113 Nov 2007Lg Electronics Inc.Method for inserting length indicator in protocol data unit of radio link control
US7304990 *2 Feb 20014 Dec 2007Bandwiz Inc.Method of encoding and transmitting data over a communication medium through division and segmentation
US731818014 Nov 20058 Jan 2008At&T Knowledge Ventures L.P.Method and system for adaptive interleaving
US732009923 Nov 200415 Jan 2008Fujitsu LimitedMethod and apparatus for generating error correction data, and a computer-readable recording medium recording an error correction data generating program thereon
US736304815 Apr 200322 Apr 2008Nokia CorporationApparatus, and associated method, for operating upon data at RLP logical layer of a communication station
US739171730 Jun 200324 Jun 2008Microsoft CorporationStreaming of variable bit rate multimedia content
US739440711 Apr 20051 Jul 2008Digital Fountain, Inc.Systematic encoding and decoding of chain reaction codes
US739845421 Dec 20048 Jul 2008Tyco Telecommunications (Us) Inc.System and method for forward error correction decoding using soft information
US740962628 Jul 20055 Aug 2008Ikanos Communications IncMethod and apparatus for determining codeword interleaver parameters
US74126411 Dec 200412 Aug 2008Digital Fountain, Inc.Protection of data from erasures using subsymbol based codes
US74186519 May 200526 Aug 2008Digital Fountain, Inc.File download and streaming system
US74513775 Oct 200611 Nov 2008Digital Fountain, Inc.Error-correcting multi-stage code generator and decoder for communication systems having single transmitters or multiple transmitters
US748344728 Jul 200527 Jan 2009Samsung Electronics Co., LtdApparatus and method for exchanging variable-length data according to radio link protocol in mobile communication system
US748348927 Jan 200327 Jan 2009Nxp B.V.Streaming multimedia data over a network having a variable bandwith
US751269726 Sep 200531 Mar 2009Digital Fountain, Inc.Scheduling of multiple files for serving on a server
US752599430 Jan 200328 Apr 2009Avaya Inc.Packet data flow identification for multiplexing
US75298064 Nov 19995 May 2009Koninklijke Philips Electronics N.V.Partitioning of MP3 content file for emulating streaming
US753213220 Aug 200712 May 2009Digital Fountain, Inc.Systematic encoding and decoding of chain reaction codes
US755500613 Sep 200430 Jun 2009The Directv Group, Inc.Method and system for adaptive transcoding and transrating in a video network
US75590041 Oct 20037 Jul 2009Sandisk CorporationDynamic redundant area configuration in a non-volatile memory system
US757066511 Jun 20024 Aug 2009Telefonaktiebolaget L M Ericsson (Publ)Generation of mixed media streams
US757470615 Dec 200311 Aug 2009Microsoft CorporationSystem and method for managing and communicating software updates
US759011830 Sep 200415 Sep 2009Agere Systems Inc.Frame aggregation format
US759742326 Jun 20066 Oct 2009Silverbrook Research Pty LtdPrinthead chip with high nozzle areal density
US761318331 Oct 20003 Nov 2009Foundry Networks, Inc.System and method for router data aggregation and delivery
US763341320 Aug 200715 Dec 2009Qualcomm IncorporatedSystems and processes for decoding a chain reaction code through inactivation
US763397022 Dec 200415 Dec 2009Agere Systems Inc.MAC header compression for use with frame aggregation
US76443359 Jun 20065 Jan 2010Qualcomm IncorporatedIn-place transformations with applications to encoding and decoding various classes of codes
US76500362 Apr 200419 Jan 2010Sharp Laboratories Of America, Inc.System and method for three-dimensional video coding
US766819829 Oct 200723 Feb 2010Lg Electronics Inc.Method for inserting length indicator in protocol data unit of radio link control
US76767359 Jun 20069 Mar 2010Digital Fountain Inc.Forward error-correcting (FEC) coding and streaming
US771106820 Aug 20074 May 2010Digital Fountain, Inc.Multi-stage code generator and decoder for communication systems
US772009630 Dec 200518 May 2010Microsoft CorporationRTP payload format for VC-1
US772017413 Feb 200618 May 2010Digital Fountain, Inc.Multi-stage code generator and decoder for communication systems
US772118411 Aug 200518 May 2010Digital Fountain, Inc.Method and apparatus for fast encoding of data symbols according to half-weight codes
US781274320 Aug 200712 Oct 2010Digital Fountain Inc.Information additive code generator and decoder for communication systems
US78318967 Sep 20049 Nov 2010Runcom Technologies, Ltd.Iterative forward error correction
US792491315 Sep 200512 Apr 2011Microsoft CorporationNon-realtime data transcoding of multimedia content
US795677223 Oct 20097 Jun 2011Qualcomm IncorporatedMethods and apparatus employing FEC codes with permanent inactivation of symbols for encoding and decoding processes
US79617005 Apr 200614 Jun 2011Qualcomm IncorporatedMulti-carrier operation in data transmission systems
US797112910 May 200728 Jun 2011Digital Fountain, Inc.Code generator and decoder for communications systems operating using hybrid codes to allow for multiple efficient users of the communications systems
US797976914 Apr 200912 Jul 2011Lg Electronics Inc.Method and apparatus for performing random access procedures
US802732826 Dec 200627 Sep 2011Alcatel LucentHeader compression in a wireless communication network
US802832214 Mar 200527 Sep 2011Time Warner Cable Inc.Method and apparatus for network content download and recording
US808171625 Jan 200720 Dec 2011Lg Electronics Inc.Digital broadcasting receiving system and method of processing data
US813507312 Dec 200313 Mar 2012Trident Microsystems (Far East) LtdEnhancing video images depending on prior image enhancements
US81857944 Jan 200722 May 2012Telefonaktiebolaget L M Ericsson (Publ)Media container file management
US818580926 Feb 200722 May 2012Digital Fountain, Inc.Multi-output packet server with independent streams
US830172512 Jan 201230 Oct 2012Apple Inc.Variant streams for real-time or near real-time streaming
US83274037 Sep 20074 Dec 2012United Video Properties, Inc.Systems and methods for providing remote program ordering on a user device via a web server
US83401331 Jun 201125 Dec 2012Lg Electronics Inc.Method of processing traffic information and digital broadcast system
US842247410 Apr 201216 Apr 2013Electronics & Telecommunications Research InstituteMethod and apparatus for transceiving data in a MIMO system
US846264315 Jul 200811 Jun 2013Qualcomm IncorporatedMIMO WLAN system
US854404319 Jul 200524 Sep 2013Qualcomm IncorporatedMethods and apparatus for providing content information to content servers
US857264624 Apr 200129 Oct 2013Visible World Inc.System and method for simultaneous broadcast for personalized messages
US861502327 Oct 201124 Dec 2013Electronics And Telecommunications Research InstituteApparatus and method for transmitting/receiving data in communication system
US863879622 Aug 200828 Jan 2014Cisco Technology, Inc.Re-ordering segments of a large number of segmented service flows
US87136247 Jun 199529 Apr 2014Personalized Media Communications LLCSignal processing apparatus and methods
US87374212 Sep 201027 May 2014Apple Inc.MAC packet data unit construction for wireless systems
US88127356 Oct 201019 Aug 2014Sony CorporationContent reproduction system, content reproduction apparatus, program, content reproduction method, and providing content server
US2001001594430 Mar 200123 Aug 2001Sony CorporationRecording method and apparatus for continuous playback of fragmented signals
US200100335869 May 200125 Oct 2001Satoru TakashimizuReceiving apparatus for digital broadcasting signal and receving/recording/reproducing apparatus thereof
US200200091371 Feb 200124 Jan 2002Nelson John E.Three-dimensional video broadcasting system
US2002005306230 Mar 20012 May 2002Ted SzymanskiTransmitter, receiver, and coding scheme to increase data rate and decrease bit error rate of an optical data link
US2002008334516 Aug 200127 Jun 2002Halliday David C.Method and system for secure communication over unstable public connections
US2002008501329 Dec 20004 Jul 2002Lippincott Louis A.Scan synchronized dual frame buffer graphics subsystem
US2002013324713 Nov 200119 Sep 2002Smith Robert D.System and method for seamlessly switching between media streams
US2002014143329 Mar 20023 Oct 2002Samsung Electronics Co., Ltd.Apparatus and method for efficiently distributing packet data channel in a mobile communication system for high rate packet transmission
US200201439533 Apr 20013 Oct 2002International Business Machines CorporationAutomatic affinity within networks performing workload balancing
US2002019111624 Apr 200119 Dec 2002Damien KesslerSystem and data format for providing seamless stream switching in a digital video recorder
US2003000538628 Jun 20012 Jan 2003Sanjay BhattNegotiated/dynamic error correction for streamed media
US2003003729916 Aug 200120 Feb 2003Smith Kenneth KayDynamic variable-length error correction code
US200300865153 Oct 20018 May 2003Francois TransChannel adaptive equalization precoding system and method
US2003010140829 Nov 200129 May 2003Emin MartinianApparatus and method for adaptive, multimode decoding
US2003010601412 Oct 20015 Jun 2003Ralf DohmenHigh speed syndrome-based FEC encoder and decoder and system using same
US2003013804329 Nov 200224 Jul 2003Miska HannukselaGrouping of image frames in video coding
US200301942119 May 200316 Oct 2003Max AbecassisIntermittently playing a video
US200302076966 May 20026 Nov 2003Serge WilleneggerMulti-media broadcast and multicast service (MBMS) in a wireless communications system
US2003022477331 May 20024 Dec 2003Douglas DeedsFragmented delivery of multimedia
US200400157686 Mar 200322 Jan 2004Philippe BordesDevice and method for inserting error correcting codes and for reconstructing data streams, and corresponding products
US200400310544 Jan 200212 Feb 2004Harald DankworthMethods in transmission and searching of video information
US2004004979310 Sep 200311 Mar 2004Chou Philip A.Multimedia presentation latency minimization
US2004008110625 Oct 200229 Apr 2004Stefan BruhnDelay trading between communication links
US2004009611020 Apr 200120 May 2004Front Porch Digital Inc.Methods and apparatus for archiving, indexing and accessing audio and video data
US200401177165 Dec 200317 Jun 2004Qiang ShenSingle engine turbo decoder with single frame size buffer for interleaving/deinterleaving
US2004015110918 Oct 20035 Aug 2004Anuj BatraTime-frequency interleaved orthogonal frequency division multiplexing ultra wide band physical layer
US2004016207118 Feb 200319 Aug 2004Francesco GrilliMethod and apparatus to track count of broadcast content recipients in a wireless telephone network
US2004020754821 Apr 200421 Oct 2004Daniel KilbankSystem and method for using a microlet-based modem
US200402403821 Apr 20032 Dec 2004Daiji IdoData reception apparatus and data distribution system
US2004025532813 Jun 200316 Dec 2004Baldwin James ArmandFast start-up for digital video streams
US2005001863513 Jul 200427 Jan 2005Ipr Licensing, Inc.Variable rate coding for forward link
US2005002806731 Jul 20033 Feb 2005Weirauch Charles R.Data with multiple sets of error correction codes
US2005007149124 Jun 200431 Mar 2005Lg Electronics Inc.Multimedia streaming service system and method
US200500840062 Apr 200421 Apr 2005Shawmin LeiSystem and method for three-dimensional video coding
US2005009169726 Oct 200428 Apr 2005Matsushita Electric Industrial Co., Ltd.Apparatus for receiving broadcast signal
US2005009721312 Mar 20045 May 2005Microsoft CorporationArchitecture for distributed sending of media data
US200501053719 Feb 200419 May 2005Johnson Mark G.Integrated circuit incorporating three-dimensional memory array with dual opposing decoder arrangement
US2005012305822 Dec 20049 Jun 2005Greenbaum Gary S.System and method for generating multiple synchronized encoded representations of media data
US2005013828624 Aug 200423 Jun 2005Franklin Chris R.In-place data transformation for fault-tolerant disk storage systems
US200501602721 Dec 200421 Jul 2005Timecertain, LlcSystem and method for providing trusted time in content of digital data files
US2005016346818 Mar 200528 Jul 2005Takao TakahashiSignal recording method & apparatus, signal recording / reproducing method & apparatus and signal recording medium
US200501804155 Mar 200318 Aug 2005Gene CheungMedium streaming distribution system
US2005019330919 Aug 20041 Sep 2005Francesco GrilliMethods for forward error correction coding above a radio link control layer and related apparatus
US200501957528 Mar 20048 Sep 2005Microsoft CorporationResolving partial media topologies
US2005020739221 Mar 200522 Sep 2005Telefonaktiebolaget Lm Ericsson (Publ)Higher layer packet framing using RLP
US2005021647229 Mar 200429 Sep 2005David LeonEfficient multicast/broadcast distribution of formatted data
US2005021695128 Jan 200529 Sep 2005Macinnis Alexander GAnticipatory video signal reception and processing
US2005025457512 May 200417 Nov 2005Nokia CorporationMultiple interoperability points for scalable media coding and transmission
US2006001556814 Jul 200419 Jan 2006Rod WalshGrouping of session objects
US2006002079628 Jun 200526 Jan 2006Microsoft CorporationHuman input security codes
US2006003173816 Oct 20039 Feb 2006Koninklijke Philips Electronics, N.V.Adaptative forward error control scheme
US2006003705724 May 200416 Feb 2006Sharp Laboratories Of America, Inc.Method and system of enabling trick play modes using HTTP GET
US2006009363422 Apr 20054 May 2006Lonza Inc.Personal care compositions and concentrates for making the same
US2006010717415 Nov 200518 May 2006Bernd HeiseSeamless change of depth of a general convolutional interleaver during transmission without loss of data
US2006010980519 Nov 200425 May 2006Nokia CorporationPacket stream arrangement in multimedia transmission
US2006012046425 Jan 20068 Jun 2006Nokia CorporationGrouping of image frames in video coding
US2006021244427 Apr 200621 Sep 2006Pandora Media, Inc.Methods and systems for utilizing contextual feedback to generate and modify playlists
US2006021278215 Mar 200521 Sep 2006Microsoft CorporationEfficient implementation of reed-solomon erasure resilient codes in high-rate applications
US200602290757 Apr 200612 Oct 2006Lg Electronics Inc.Supporting handover of mobile terminal
US2006024482429 Jun 20062 Nov 2006Debey Henry CMethod and system of program transmission optimization using a redundant transmission sequence
US2006024486525 May 20062 Nov 2006Rohde & Schwarz, Inc.Apparatus, systems, methods and computer products for providing a virtual enhanced training sequence
US2006024819526 Apr 20062 Nov 2006Kunihiko ToumuraComputer system with a packet transfer device using a hash value for transferring a content request
US2006025685113 Apr 200616 Nov 2006Nokia CorporationCoding, storage and signalling of scalability information
US2007000295328 Jun 20064 Jan 2007Kabushiki Kaisha ToshibaEncoded stream reproducing apparatus
US2007000627415 Jun 20064 Jan 2007Toni PailaTransmission and reception of session packets
US200700165944 Apr 200618 Jan 2007Sony CorporationScalable video coding (SVC) file format
US2007002221518 Jul 200625 Jan 2007Singer David WMethod and apparatus for media data transmission
US2007002809913 Mar 20061 Feb 2007Bamboo Mediacasting Ltd.Secure multicast transmission
US2007007887627 Jan 20065 Apr 2007Yahoo! Inc.Generating a stream of media data containing portions of media files using location tags
US2007008156211 Oct 200612 Apr 2007Hui MaMethod and device for stream synchronization of real-time multimedia transport over packet network
US200701100742 Jan 200617 May 2007Bob BradleySystem and Method for Synchronizing Media Presentation at Multiple Recipients
US200701403699 Feb 200721 Jun 2007Limberg Allen LSystem of robust DTV signal transmissions that legacy DTV receivers will disregard
US2007016256830 Jun 200612 Jul 2007Manish GuptaDynamic media serving infrastructure
US200701626115 Jan 200712 Jul 2007Google Inc.Discontinuous Download of Media Files
US2007017680030 Jan 20062 Aug 2007International Business Machines CorporationFast data stream decoding using apriori information
US2007017781112 Jan 20072 Aug 2007Lg Electronics Inc.Processing multiview video
US2007018597320 Nov 20069 Aug 2007Dot Hill Systems, Corp.Pull data replication model
US2007019589413 Feb 200723 Aug 2007Digital Fountain, Inc.Multiple-field based code generator and decoder for communications systems
US2007020094920 Feb 200730 Aug 2007Qualcomm IncorporatedRapid tuning in multimedia applications
US2007020154911 Jan 200730 Aug 2007Nokia CorporationBackward-compatible aggregation of pictures in scalable video coding
US2007020419613 Feb 200730 Aug 2007Digital Fountain, Inc.Streaming and buffering using variable fec overhead and protection periods
US2007023056829 Mar 20074 Oct 2007Alexandros EleftheriadisSystem And Method For Transcoding Between Scalable And Non-Scalable Video Codecs
US200702337844 Jun 20074 Oct 2007Microsoft CorporationWrapper Playlists on Streaming Media Services
US2007025584427 Apr 20061 Nov 2007Microsoft CorporationGuided random seek support for media streaming
US2007027720924 May 200629 Nov 2007Newport Media, Inc.Robust transmission system and method for mobile television applications
US2008001015324 Apr 200710 Jan 2008Pugh-O'connor ArchieComputer network provided digital content under an advertising and revenue sharing basis, such as music provided via the internet with time-shifted advertisements presented by a client resident application
US2008003427323 Apr 20077 Feb 2008Digital Fountain, Inc.Information additive code generator and decoder for communication systems
US200800527532 Jul 200728 Feb 2008Mediatek Inc.Systems and methods for managing television (tv) signals
US2008005895816 May 20076 Mar 2008Chia Pao ChengKnee joint with retention and cushion structures
US2008005953231 Oct 20076 Mar 2008Kazmi Syed NMethod and system for managing digital content, including streaming media
US2008006613624 Aug 200613 Mar 2008International Business Machines CorporationSystem and method for detecting topic shift boundaries in multimedia streams using joint audio, visual and text cues
US2008007517217 Sep 200727 Mar 2008Kabushiki Kaisha ToshibaMotion picture encoding apparatus and method
US200800867511 Jun 200710 Apr 2008Digital Fountain, Inc.Methods and apparatus for scheduling, serving, receiving media-on-demand for clients, servers arranged according to constraints on resources
US2008010147824 Oct 20071 May 2008Kabushiki Kaisha ToshibaDecoding device and decoding method
US2008013400514 Jun 20055 Jun 2008Izzat Hekmat IzzatAdaptive Forward Error Correction
US2008017056414 Nov 200717 Jul 2008Qualcomm IncorporatedSystems and methods for channel switching
US200801708067 Jan 200817 Jul 2008Samsung Electronics Co., Ltd.3D image processing apparatus and method
US2008017243011 Jan 200717 Jul 2008Andrew Thomas ThorstensenFragmentation Compression Management
US2008017271210 Jan 200817 Jul 2008Matsushita Electric Industrial Co., Ltd.Multimedia data transmitting apparatus, multimedia data receiving apparatus, multimedia data transmitting method, and multimedia data receiving method
US2008018129615 Mar 200731 Jul 2008Dihong TianPer multi-block partition breakpoint determining for hybrid variable length coding
US200801894192 Feb 20077 Aug 2008David Andrew GirleSystem and Method to Synchronize OSGi Bundle Inventories Between an OSGi Bundle Server and a Client
US200801928189 Feb 200714 Aug 2008Dipietro Donald VincentSystems and methods for securing media
US2008021531730 Jan 20084 Sep 2008Dts, Inc.Lossless multi-channel audio codec using adaptive segmentation with random access point (RAP) and multiple prediction parameter set (MPPS) capability
US2008023235719 Mar 200725 Sep 2008Legend Silicon Corp.Ls digital fountain code
US2008024391825 Mar 20052 Oct 2008Koninklijke Philips Electronic, N.V.System and Method For Supporting Improved Trick Mode Performance For Disc Based Multimedia Content
US2008025641815 Apr 200816 Oct 2008Digital Fountain, IncDynamic stream interleaving and sub-stream based delivery
US2008028194311 Feb 200813 Nov 2008Jody ShapiroSystem, method, and computer program product for remotely determining the configuration of a multi-media content user
US2008028555614 May 200820 Nov 2008Samsung Electronics Co., Ltd.Broadcasting service transmitting apparatus and method and broadcasting service receiving apparatus and method for effectively accessing broadcasting service
US2008030389310 Jun 200811 Dec 2008Samsung Electronics Co., Ltd.Method and apparatus for generating header information of stereoscopic image data
US200803131918 Jan 200818 Dec 2008Nokia CorporationMethod for the support of file versioning in file repair
US2009000343925 Jun 20081 Jan 2009Nokia CorporationSystem and method for indicating temporal layer switching points
US2009001922910 Jul 200715 Jan 2009Qualcomm IncorporatedData Prefetch Throttle
US2009003119925 Aug 200829 Jan 2009Digital Fountain, Inc.File download and streaming system
US200900439066 Aug 200712 Feb 2009Hurst Mark BApparatus, system, and method for multi-bitrate content streaming
US2009005570531 Jan 200726 Feb 2009Wen GaoDecoding of Raptor Codes
US2009006755112 Sep 200812 Mar 2009Digital Fountain, Inc.Generating and communicating source identification information to enable reliable communications
US200900838062 Dec 200826 Mar 2009Microsoft CorporationMedia organization for distributed sending of media data
US2009008944528 Sep 20072 Apr 2009Deshpande Sachin GClient-Controlled Adaptive Streaming
US200900921389 Oct 20089 Apr 2009Samsung Electronics Co. Ltd.Apparatus and method for generating and parsing mac pdu in a mobile communication system
US2009010049624 Apr 200716 Apr 2009Andreas BechtolsheimMedia server system
US2009010352325 Aug 200823 Apr 2009Rebelvox, LlcTelecommunication and multimedia management method and apparatus
US2009010635616 Oct 200823 Apr 2009Swarmcast, Inc.Media playback point seeking using data range requests
US2009012563613 Nov 200714 May 2009Qiong LiPayload allocation methods for scalable multimedia servers
US200901505574 Dec 200811 Jun 2009Swarmcast, Inc.Dynamic bit rate scaling
US2009015811415 Oct 200818 Jun 2009Digital Fountain, Inc.Error-correcting multi-stage code generator and decoder for communication systems having single transmitters or multiple transmitters
US2009016465324 Dec 200725 Jun 2009Mandyam Giridhar DAdaptive streaming for on demand wireless services
US200901897923 Apr 200930 Jul 2009Shokrollahi M AminSystematic encoding and decoding of chain reaction codes
US200902019902 Feb 200913 Aug 2009Alcatel-LucentMethod and device for reordering and multiplexing multimedia packets from multimedia streams pertaining to interrelated sessions
US2009020487713 Feb 200813 Aug 2009Innovation Specialists, LlcBlock Modulus Coding (BMC) Systems and Methods for Block Coding with Non-Binary Modulus
US2009021054712 Feb 200920 Aug 2009Digital Fountain, Inc.Scheduling of multiple files for serving on a server
US2009022287330 Dec 20053 Sep 2009Einarsson TorbjoernMultimedia Channel Switching
US2009024869731 Mar 20081 Oct 2009Richardson David RCache optimization
US200902575089 Mar 200915 Oct 2009Gaurav AggarwalMethod and system for enabling video trick modes
US2009028784111 May 200919 Nov 2009Swarmcast, Inc.Live media delivery over a packet-based computer network
US200902971237 Aug 20083 Dec 2009Microsoft CorporationMedia streaming with enhanced seek operation
US200903002037 Aug 20083 Dec 2009Microsoft CorporationStream selection for enhanced media streaming
US200903002047 Aug 20083 Dec 2009Microsoft CorporationMedia streaming using an index file
US200903075659 Dec 200810 Dec 2009Digital Fountain, Inc.Method and apparatus for fast encoding of data symbols according to half-weight codes
US2009031956321 Jun 200824 Dec 2009Microsoft CorporationFile format for media distribution and presentation
US2009032822827 Jun 200831 Dec 2009Microsoft CorporationSegmented Media Content Rights Management
US2010001106131 Jul 200914 Jan 2010Hudson Michael DCentralized selection of peers as media data sources in a dispersed peer network
US2010001111719 Mar 200914 Jan 2010Apple Inc.Video streaming using multiple channels
US2010001127411 Jun 200914 Jan 2010Qualcomm IncorporatedHypothetical fec decoder and signalling for decoding control
US2010002087120 Apr 200928 Jan 2010Nokia CorporationMethod and Device for Video Coding and Decoding
US201000235254 Jan 200728 Jan 2010Magnus WesterlundMedia container file management
US2010004986516 Apr 200925 Feb 2010Nokia CorporationDecoding Order Recovery in Session Multiplexing
US201000614445 Dec 200811 Mar 2010On2 Technologies Inc.System and method for video encoding using adaptive segmentation
US2010006749530 Oct 200718 Mar 2010Young Dae LeeMethod of performing random access in a wireless communcation system
US2010013167123 Nov 200927 May 2010Jaspal KohliAdaptive network content delivery system
US2010015357815 Jul 200917 Jun 2010Nokia CorporationMethod and Apparatus for Peer to Peer Streaming
US2010017482318 Mar 20108 Jul 2010Juniper Networks, Inc.Optimizing batch size for prefetching data over wide area networks
US2010018913123 Jan 200929 Jul 2010Verivue, Inc.Scalable seamless digital video stream splicing
US201001989828 Feb 20105 Aug 2010Clarity Systems, S.L.Methods for Transmitting Multimedia Files and Advertisements
US2010021169012 Feb 201019 Aug 2010Digital Fountain, Inc.Block partitioning for a data stream
US2010022353326 Feb 20102 Sep 2010Qualcomm IncorporatedMobile reception of digital video broadcasting-terrestrial services
US2010023547216 Mar 200916 Sep 2010Microsoft CorporationSmooth, stateless client media streaming
US2010023552816 Mar 200916 Sep 2010Microsoft CorporationDelivering cacheable streaming media presentations
US2010025705115 Apr 20107 Oct 2010Media Patents, S.L.Apparatus and methods for the on-line distribution of digital files
US2010031863216 Jun 200916 Dec 2010Microsoft CorporationByte range caching
US2011001976917 May 201027 Jan 2011Qualcomm IncorporatedMulti stage code generator and decoder for communication systems
US2011005588112 May 20093 Mar 2011Tencent Technology (Shenzhen) Company LimitedMedia file on-demand method, system and appartus
US201100831445 Nov 20097 Apr 2011Bocharov John AIntegrating continuous and sparse streaming data
US2011009682821 Sep 201028 Apr 2011Qualcomm IncorporatedEnhanced block-request streaming using scalable encoding
US2011010351928 Aug 20095 May 2011Qualcomm IncorporatedSystems and processes for decoding chain reaction codes through inactivation
US201101193944 Nov 201019 May 2011Futurewei Technologies, Inc.System and Method for Media Content Streaming
US2011011939615 Nov 201019 May 2011Samsung Electronics Co., Ltd.Method and apparatus for transmitting and receiving data
US201102165414 Mar 20118 Sep 2011Ushio Denki Kabushiki KaishaLight source apparatus
US2011023151921 Sep 201022 Sep 2011Qualcomm IncorporatedEnhanced block-request streaming using url templates and construction rules
US2011023156921 Sep 201022 Sep 2011Qualcomm IncorporatedEnhanced block-request streaming using block partitioning or request controls for improved client-side handling
US2011023878921 Sep 201029 Sep 2011Qualcomm IncorporatedEnhanced block-request streaming system using signaling or block creation
US2011023907821 Sep 201029 Sep 2011Qualcomm IncorporatedEnhanced block-request streaming using cooperative parallel http and forward error correction
US2011025851027 Jun 201120 Oct 2011Digital Fountain, Inc.Code generator and decoder for communications systems operating using hybrid codes to allow for multiple efficient uses of the communications systems
US2011026817818 Aug 20093 Nov 2011Anthony Neal ParkEncoding video streams for adaptive video streaming
US2011028031125 Feb 201117 Nov 2011Qualcomm IncorporatedOne-stream coding for asymmetric stereo video
US2011028031625 Feb 201117 Nov 2011Qualcom IncorporatedFrame packing for asymmetric stereo video
US2011029962918 Aug 20108 Dec 2011Qualcomm IncorporatedMethods and apparatus employing fec codes with permanent inactivation of symbols for encoding and decoding processes
US2011030754510 Dec 201015 Dec 2011Nokia CorporationApparatus and Methods for Describing and Timing Representatives in Streaming Media Files
US2011030758114 Jun 201015 Dec 2011Research In Motion LimitedMedia Presentation Description Delta File For HTTP Streaming
US201200137466 Jan 201119 Jan 2012Qualcomm IncorporatedSignaling data for multiplexing video components
US2012001696518 Feb 201119 Jan 2012Qualcomm IncorporatedVideo switching for streaming video data
US201200204137 Apr 201126 Jan 2012Qualcomm IncorporatedProviding frame packing type information for video coding
US2012002324920 Jul 201026 Jan 2012Qualcomm IncorporatedProviding sequence data sets for streaming video data
US2012002325420 Jul 201126 Jan 2012University-Industry Cooperation Group Of Kyung Hee UniversityMethod and apparatus for providing multimedia streaming service
US201200337309 Aug 20109 Feb 2012Sony Computer Entertainment America, LLC.Random access point (rap) formation using intra refreshing technique in video coding
US201200420508 Aug 201116 Feb 2012Qualcomm IncorporatedRepresentation groups for network streaming of coded multimedia data
US201200420898 Aug 201116 Feb 2012Qualcomm IncorporatedTrick modes for network streaming of coded multimedia data
US201200420908 Aug 201116 Feb 2012Qualcomm IncorporatedManifest file updates for network streaming of coded multimedia data
US2012004728019 Aug 201123 Feb 2012University-Industry Cooperation Group Of Kyung Hee UniversityMethod and apparatus for reducing deterioration of a quality of experience of a multimedia service in a multimedia system
US201200995934 Mar 201126 Apr 2012Qualcomm IncorporatedUniversal file delivery methods for providing unequal error protection and bundled file delivery services
US201201513029 Aug 201114 Jun 2012Qualcomm IncorporatedBroadcast multimedia storage and access using page maps when asymmetric memory is used
US2012018553022 Jul 201019 Jul 2012Jigsee Inc.Method of streaming media to heterogeneous client devices
US2012020253512 Apr 20129 Aug 2012Navin ChaddhaMethod And System For Communicating A Data File
US2012020706811 Feb 201116 Aug 2012Qualcomm IncorporatedFraming for an improved radio link protocol including fec
US2012020858011 Feb 201116 Aug 2012Qualcomm IncorporatedForward error correction scheduling for an improved radio link protocol
US2012031730516 Feb 201113 Dec 2012Telefonaktiebolaget Lm Ericsson (Publ)Method and Arrangement for Representation Switching in HTTP Streaming
US2013000248313 Sep 20123 Jan 2013Qualcomm IncorporatedMethods and systems for deriving seed position of a subscriber station in support of unassisted gps-type position determination in a wireless communication system
US2013000722326 Apr 20123 Jan 2013Qualcomm IncorporatedEnhanced block-request streaming system for handling low-latency streaming
US2013006729529 Feb 201214 Mar 2013Digital Fountain, Inc.File download and streaming system
US201300912514 Oct 201211 Apr 2013Qualcomm IncorporatedNetwork streaming of media data
US2013024664310 Jul 201219 Sep 2013Qualcomm IncorporatedSwitch signaling methods providing improved switching between representations for adaptive http streaming
US2013025463429 Jan 201326 Sep 2013Qualcomm IncorporatedUniversal object delivery and template-based file delivery
US2013028702318 Jun 201331 Oct 2013Apple Inc.Multimedia-aware quality-of-service and error correction provisioning
US201400095786 Sep 20139 Jan 2014Qualcomm IncorporatedProviding frame packing type information for video coding
US201403801134 Apr 201425 Dec 2014Qualcomm IncorporatedEnhanced block-request streaming using cooperative parallel http and forward error correction
USRE4374117 Nov 201116 Oct 2012Qualcomm IncorporatedSystematic encoding and decoding of chain reaction codes
CN1338839A9 Aug 20016 Mar 2002扎尔林克半导体股份有限公司Codes for combining Reed-Solomen and Teb Technologies
CN1425228A16 Nov 200018 Jun 2003讯捷通讯公司Variable rate coding for forward link
CN1481643A14 Dec 200110 Mar 2004英国电讯有限公司Transmission and reception of audio and/or video material
CN1708934A16 Oct 200314 Dec 2005皇家飞利浦电子股份有限公司Adaptative forward error control scheme
CN1714577A18 Nov 200328 Dec 2005英国电讯有限公司Transmission of video
CN1792056A14 May 200421 Jun 2006高通股份有限公司Reliable reception of broadcast/multicast content
CN1806392A20 Jan 200519 Jul 2006三星电子株式会社Apparatus and method for generating and decoding forward error correction codes having variable rate in a high-rate wireless data communication system
CN1819661A22 Jan 200316 Aug 2006诺基亚有限公司Grouping of image frames in video coding
CN101390399A11 Jan 200718 Mar 2009诺基亚公司Backward-compatible aggregation of pictures in scalable video coding
CN101729857A24 Nov 20099 Jun 2010中兴通讯股份有限公司Method for accessing video service and video playing system
EP0669587A215 Feb 199530 Aug 1995AT&amp;T Corp.Networked system for display of multimedia presentations
EP0701371A125 Aug 199513 Mar 1996International Business Machines CorporationVideo optimised media streamer
EP0784401A213 Jan 199716 Jul 1997Kabushiki Kaisha ToshibaDigital broadcast receiving terminal apparatus
EP0853433A122 Aug 199515 Jul 1998Macrovision CorporationMethod and apparatus for detecting a source identification signal in a video signal
EP0854650A214 Nov 199722 Jul 1998NOKIA TECHNOLOGY GmbHMethod for addressing a service in digital video broadcasting
EP0903955A14 Sep 199724 Mar 1999SGS-THOMSON MICROELECTRONICS S.r.l.Modular architecture PET decoder for ATM networks
EP0986908A111 Mar 199822 Mar 2000Northern Telecom LimitedDynamic selection of media streams for display
EP1051027A14 May 20008 Nov 2000Sony CorporationMethods and apparatus for data processing, methods and apparatus for data reproducing and recording media
EP1124344A126 Jul 200016 Aug 2001Matsushita Electric Industrial Co., Ltd.Ofdm communication device
EP1241795A217 Sep 199918 Sep 2002Digital FountainMethod and system for transmitting and receiving information using chain reaction codes
EP1298931A220 Sep 20022 Apr 2003Oplayo OyAdaptive media stream
EP1406452A226 Sep 20037 Apr 2004NTT DoCoMo, Inc.Video signal encoding and decoding method
EP1455504A25 Mar 20048 Sep 2004Samsung Electronics Co., Ltd.Apparatus and method for processing audio signal and computer readable recording medium storing computer program for the method
EP1468497A123 Dec 200220 Oct 2004Digital Fountain, Inc.Multi; stage code generator and decoder for communication systems
EP1670256A223 Nov 200514 Jun 2006Microsoft CorporationA system and process for controlling the coding bit rate of streaming media data
EP1700410B12 Dec 200428 Apr 2010Adaptive Spectrum and Signal Alignment, Inc.Adaptive fec codeword management
EP1755248A119 Aug 200521 Feb 2007BenQ Mobile GmbH & Co. OHGIndication of lost segments across layer boundaries
EP2071827A214 Dec 200117 Jun 2009British Telecommunications Public Limited CompanyTransmission and reception of audio and/or video material
JP3809957B2 Title not available
JP3976163B2 Title not available
JP8289255A Title not available
JP9252253A Title not available
JP2000151426A Title not available
JP2000216835A Title not available
JP2000307435A Title not available
JP2000353969A Title not available
JP2000513164A Title not available
JP2001036417A Title not available
JP2001094625A Title not available
JP2001189665A Title not available
JP2001223655A Title not available
JP2001251287A Title not available
JP2001274776A Title not available
JP2001274855A Title not available
JP2002073625A Title not available
JP2002204219A Title not available
JP2002543705A Title not available
JP2003092564A Title not available
JP2003174489A Title not available
JP2003256321A Title not available
JP2003318975A Title not available
JP2003319012A Title not available
JP2003333577A Title not available
JP2003507985A Title not available
JP2003510734A Title not available
JP2004048704A Title not available
JP2004070712A Title not available
JP2004135013A Title not available
JP2004165922A Title not available
JP2004192140A Title not available
JP2004193992A Title not available
JP2004289621A Title not available
JP2004343701A Title not available
JP2004348824A Title not available
JP2004362099A Title not available
JP2004516717A Title not available
JP2004529533A Title not available
JP2005094140A Title not available
JP2005136546A Title not available
JP2005204170A Title not available
JP2005223433A Title not available
JP2005277950A Title not available
JP2005514828T Title not available
JP2006074335A Title not available
JP2006074421A Title not available
JP2006115104A Title not available
JP2006174032A Title not available
JP2006174045A Title not available
JP2006186419A Title not available
JP2006287422A Title not available
JP2006319743A Title not available
JP2006503463A Title not available
JP2006505177A Title not available
JP2006506926A Title not available
JP2006519517A Title not available
JP2007013675A Title not available
JP2007089137A Title not available
JP2007158592A Title not available
JP2007174170A Title not available
JP2007228205A Title not available
JP2007520961A Title not available
JP2008011404A Title not available
JP2008016907A Title not available
JP2008283232A Title not available
JP2008283571A Title not available
JP2008502212A Title not available
JP2008508761A Title not available
JP2008508762A Title not available
JP2008543142A Title not available
JP2008546361A Title not available
JP2009027598A Title not available
JP2009171558A Title not available
JP2009277182A Title not available
JP2009522921A Title not available
JP2009522922A Title not available
JP2009527949A Title not available
JP2009544991A Title not available
JP2010539832A Title not available
JP2011087103A Title not available
JPH1141211A Title not available
JPH07183873A Title not available
JPH08186570A Title not available
JPH11112479A Title not available
JPH11164270A Title not available
KR100809086B1 Title not available
KR20030071815A Title not available
KR20030074386A Title not available
KR20040107152A Title not available
KR20040107401A Title not available
KR20050009376A Title not available
KR20080083299A Title not available
KR20090098919A Title not available
RU2189629C2 Title not available
RU2265960C2 Title not available
RU2290768C1 Title not available
RU2297663C2 Title not available
RU2312390C2 Title not available
RU2357279C2 Title not available
RU99117925A Title not available
TWI246841B Title not available
TWI354908B Title not available
TWI355168B Title not available
WO1996034463A129 Apr 199631 Oct 1996Trustees Of The Stevens Institute Of TechnologyHigh integrity transport for time critical multimedia networking applications
WO1997050183A125 Jun 199731 Dec 1997Telefonaktiebolaget Lm Ericsson (Publ)Variable length coding with error protection
WO1998004973A118 Jul 19975 Feb 1998Zenith Electronics CorporationData de-rotator and de-interleaver
WO1998032231A119 Dec 199723 Jul 1998Qualcomm IncorporatedMethod and apparatus for transmitting and receiving concatenated code data
WO1998032256A113 Jan 199823 Jul 1998Telefonaktiebolaget Lm Ericsson (Publ)Apparatus, and associated method, for transmitting and receiving a multi-stage, encoded and interleaved digital communication signal
WO2000014921A123 Aug 199916 Mar 2000At & T Corp.Combined channel coding and space-block coding in a multi-antenna arrangement
WO2000018017A917 Sep 199920 Dec 2001Digital FountainLost packet recovery method for packet transmission protocols
WO2000052600A13 Mar 20008 Sep 2000Sony CorporationTransmitter, receiver, transmitter/receiver system, transmission method and reception method
WO2001020786A115 Sep 200022 Mar 2001Digital FountainGroup chain reaction encoder with variable number of associated input data for each output group code
WO2001057667A12 Feb 20019 Aug 2001Bandwiz, Inc.Data streaming
WO2001058130A22 Feb 20019 Aug 2001Bandwiz, Inc.Coding method
WO2001058131A22 Feb 20019 Aug 2001Bandwiz, Inc.Broadcast system
WO2002027988A225 Sep 20014 Apr 2002Visible World, Inc.System and method for seamless switching
WO2002047391A19 Nov 200113 Jun 2002Digital Fountain, Inc.Methods and apparatus for scheduling, serving, receiving media-on-demand for clients, servers arranged according to constraints on resources
WO2002063461A18 Feb 200215 Aug 2002Nokia CorporationMethod and system for buffering streamed data
WO2003046742A121 Nov 20025 Jun 2003Nokia CorporationSystem and method for identifying and accessing network services
WO2003056703A123 Dec 200210 Jul 2003Digital Fountain, Inc.Multi-stage code generator and decoder for communication systems
WO2003105350A110 Jun 200318 Dec 2003Digital Fountain, Inc.Decoding of chain reaction codes through inactivation of recovered symbols
WO2003105484A111 Jun 200218 Dec 2003Telefonaktiebolaget L M Ericsson (Publ)Generation of mixed media streams
WO2004015948A113 Aug 200219 Feb 2004Nokia CorporationSymbol interleaving
WO2004019521A130 Jul 20034 Mar 2004Sharp Kabushiki KaishaData communication device, its intermittent communication method, program describing its method, and recording medium on which program is recorded
WO2004030273A127 Sep 20028 Apr 2004Fujitsu LimitedData delivery method, system, transfer method, and program
WO2004034589A21 Oct 200322 Apr 2004Digital Fountain, Inc.Systematic encoding and decoding of chain reaction codes
WO2004036824A110 Oct 200329 Apr 2004Nokia CorporationStreaming media
WO2004040831A116 Oct 200313 May 2004Koninklijke Philips Electronics N.V.Adaptative forward error control scheme
WO2004047019A221 Nov 20033 Jun 2004Electronics And Telecommunications Research InstituteEncoder using low density parity check codes and encoding method thereof
WO2004047455A118 Nov 20033 Jun 2004British Telecommunications Public Limited CompanyTransmission of video
WO2004088988A126 Mar 200414 Oct 2004Sharp Kabushiki KaishaVideo encoder and method of encoding video
WO2004109538A110 Mar 200416 Dec 2004Samsung Electronics Co. Ltd.Apparatus and method for organization and interpretation of multimedia data on a recording medium
WO2005036753A26 Oct 200421 Apr 2005Digital Fountain, Inc.Error-correcting multi-stage code generator and decoder for communication systems having single transmitters or multiple transmitters
WO2005041421A129 Sep 20046 May 2005Telefonaktiebolaget L M Ericsson (Publ)In-place data deinterleaving
WO2005078982A111 Feb 200525 Aug 2005Nokia CorporationIdentification and re-transmission of missing parts
WO2005107123A119 Apr 200510 Nov 2005Thomson Licensing SaMethod of transmitting digital data packets and device implementing the method
WO2005112250A29 May 200524 Nov 2005Digital Fountain, Inc.File download and streaming system
WO2006013459A127 Jul 20059 Feb 2006Nokia CorporationPoint-to-point repair request mechanism for point-to-multipoint transmission systems
WO2006020826A211 Aug 200523 Feb 2006Digital Fountain, Inc.Method and apparatus for fast encoding of data symbols according to half-weight codes
WO2006036276A121 Jul 20056 Apr 2006Qualcomm IncorporatedMethods and apparatus for providing content information to content servers
WO2006057938A221 Nov 20051 Jun 2006Thomson Research Funding CorporationMethod and apparatus for channel change in dsl system
WO2006060036A114 Jun 20058 Jun 2006Thomson LicensingAdaptive forward error correction
WO2006084503A18 Feb 200517 Aug 2006Telefonaktiebolaget Lm Ericsson (Publ)On-demand multi-channel streaming session over packet-switched networks
WO2006116102A221 Apr 20062 Nov 2006Qualcomm IncorporatedMulti-carrier operation in data transmission systems
WO2006135878A212 Jun 200621 Dec 2006Digital Fountain, Inc.In-place transformations with applications to encoding and decoding various classes of codes
WO2007078253A24 Jan 200712 Jul 2007Telefonaktiebolaget Lm Ericsson (Publ)Media container file management
WO2007090834A26 Feb 200716 Aug 2007Telefonaktiebolaget Lm Ericsson (Publ)Transporting packets
WO2007098397A216 Feb 200730 Aug 2007Digital Fountain, Inc.Multiple-field based code generator and decoder for communications systems
WO2007098480A121 Feb 200730 Aug 2007Qualcomm IncorporatedRapid tuning in multimedia applications
WO2008011549A220 Jul 200724 Jan 2008Sandisk CorporationContent distribution system
WO2008023328A320 Aug 200724 Apr 2008Nokia CorpSystem and method for indicating track relationships in media files
WO2008054100A129 Oct 20078 May 2008Electronics And Telecommunications Research InstituteMethod and apparatus for decoding metadata used for playing stereoscopic contents
WO2008085013A111 Jan 200817 Jul 2008University-Industry Cooperation Group Of Kyung Hee UniversityPacket format of network abstraction layer unit, and algorithm and apparatus for video encoding and decoding using the format, qos control algorithm and apparatus for ipv6 label switching using the format
WO2008086313A17 Jan 200817 Jul 2008Divx, Inc.Video distribution system including progressive playback
WO2008131023A116 Apr 200830 Oct 2008Digital Fountain, Inc.Dynamic stream interleaving and sub-stream based delivery
WO2008144004A116 May 200827 Nov 2008Thomson LicensingApparatus and method for encoding and decoding signals
WO2009065526A113 Nov 200828 May 2009Media Patents S.L.A process for the on-line distribution of audiovisual contents with advertisements, advertisement management system, digital rights management system and audiovisual content player provided with said systems
WO2009137705A27 May 200912 Nov 2009Digital Fountain, Inc.Fast channel zapping and high quality streaming protection over a broadcast channel
WO2009143741A112 May 20093 Dec 2009腾讯科技(深圳)有限公司Method, system and apparatus for playing media files on demand
WO2010085361A226 Jan 201029 Jul 2010Thomson LicensingFrame packing for video coding
WO2011038013A222 Sep 201031 Mar 2011Qualcomm IncorporatedEnhanced block-request streaming system using signaling or block creation
WO2011038034A122 Sep 201031 Mar 2011Qualcomm IncorporatedEnhanced block-request streaming using cooperative parallel http and forward error correction
WO2011059286A215 Nov 201019 May 2011Samsung Electronics Co.,Ltd.Method and apparatus for providing and receiving data
WO2011070552A110 Dec 201016 Jun 2011Nokia CorporationApparatus and methods for describing and timing representations in streaming media files
WO2011102792A116 Feb 201125 Aug 2011Telefonaktiebolaget L M Ericsson (Publ)Method and arrangement for adaption in http streaming
WO2012021540A19 Aug 201116 Feb 2012Qualcomm IncorporatedTrick modes for network streaming of coded video data
Non-Patent Citations
Reference
1"Digital Video Broadcasting (DVB); Framing structure, channel coding and modulation for digital terrestrial television; ETSI EN 300 744" ETSI Standards, LIS, Sophia Antipolis Cedex, France, V1.6.1, pp. 9, 10 Jan. 2009.
2"Digital Video Broadcasting (DVB); Guidelines for the implementation of DVB-IP Phase 1 specifications; ETSI TS 102 542" ETSI Standards, LIS, Sophia Antipoliscedex, France, vol. BC, No. V1.2.1, Apr. 1, 2008, XP014041619 ISSN: 0000-0001 p. 43 p. 66 pp. 70, 71.
3"RaptorQ Technical Overview", Qualcomm Incorporated, pp. 1-12 (Oct. 1, 2010).
43GPP TS 26.234 V9.1.0 ,"3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Transparent end-to-end Packet-switched Streaming Service (PSS); Protocols and codecs (Release 9)", Dec. 2009, 179 pages.
53GPP TS 26.244 V9.1.0, 3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Transparent end-to-end packet switched streaming service (PSS); 3GPP file format (3GP), (Release 9), Mar. 2010, 55 pages.
63GPP TS 26.247, v1.5.0, 3rd Generation Partnership Project; Technical Specification Group Services and System Aspects Transparent end-to-end Packet-switched Streaming Service (PSS); Progressive Download and Dynamic Adaptive Streaming over HTTP (3GP-DASH) (Release 10), 2010, 91 pages.
73GPP TSG-SA4 #57 S4-100015, IMS based PSS and MBMS User Service extensions, Jan.19, 2010, URL: http://www.3gpp.org/ftp/tsg-sa/ZWG4 Codec/TSGS4 57/docs/S4-100015.zip.
83GPP: "3rd Generation Partnership Project; Technical Specification Group Services and system Aspects; Multimedia Broadcast/Multicast Service (MBMS); Protocols and codecs (Release 6)", Sophia Antipolis, France, Jun. 1, 2005, XP002695256, Retrieved from the Internet: URL:http://www.etsi.org/deliver/etsi-ts/126300-126399/126346/06.01.00-60/ts-126346v060100p.pdf.
93rd Generation Partnership Project, Technical Specification Group Services and System Aspects Transparent end-to-end packet switched streaming service (PSS), 3GPP file format (3GP) (Release 9 ) , 3GPP Standard, 3GPP TS 26.244, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre , 650, Route Des Lucioles , F-06921 Sophia-Antipolis Cedex , France, No. V8.1.0, Jun. 1, 2009, pp. 1-52, XP050370199.
103rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Transparent end-to-end packet switched streaming service (PSS); 3GPP file format (3GP) (Release 9), 3GPP Standard; 3GPP TS 26.244, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, No. V9.2.0, Jun. 9, 2010, pp. 1-55, XP050441544, [retrieved on Jun. 9, 2010].
113rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Transparent end-to-end Packet-switched Streaming Service (PSS); Progressive Download and Dynamic Adaptive Streaming over HTTP (3GP-DASH) (Release 10), 3GPP Standard; 3GPP TS 26.247, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre ; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, vol. SA WG4, No. V10.0.0, Jun. 17, 2011, pp. 1-94, XP050553206, [retrieved on Jun. 17, 2011].
123rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Transparent end-to-end Packet-switched Streaming Service (PSS);Protocols and codecs(Release 9) 3GPP TS 26.234 V9.3.0, Jun. 23, 2010 P.85- 102,URL, http://www.3gpp.org/ftp/TSG-SA/WG4-Codec/TSGS4-59/Docs/S4-100511.zip, 26234-930.zip.
13Aggarwal, C. et al.: "A Permutation-Based Pyramid Broadcasting Scheme for Video-on-Demand Systems," Proc. IEEE Int'l Conf. on Multimedia Systems, Hiroshima, Japan (Jun. 1996).
14Aggarwal, C. et al.: "On Optimal Batching Policies for Video-on-Demand Storage Servers," Multimedia Systems, vol. 4, No. 4, pp. 253-258 (1996).
15Albanese, A., et al., "Priority Encoding Transmission", IEEE Transactions on Information Theory, vol. 42, No. 6, pp. 1-22, (Nov. 1996).
16Alex Zambelli,"IIS Smooth Streaming Technical Overview", Microsoft Mar. 25, 2009, XP002620446, Retrieved from the Internet: URL:http://www.microsoft.com/downloads/en/ details.aspx″FamilyID=03d22583-3ed6-44da-8464-blb4b5ca7520, [retrieved on Jan. 21, 2011].
17Alex Zambelli,"IIS Smooth Streaming Technical Overview", Microsoft Mar. 25, 2009, XP002620446, Retrieved from the Internet: URL:http://www.microsoft.com/downloads/en/ details.aspx''FamilyID=03d22583-3ed6-44da-8464-blb4b5ca7520, [retrieved on Jan. 21, 2011].
18Almeroth, et al., "The use of multicast delivery to provide a scalable and interactive video-on-demand service", IEEE Journal on Selected Areas in Communication, 14(6): 1110-1122, (1996).
19Alon, et al.: "Linear Time Erasure Codes with Nearly Optimal Recovery," Proceedings of the Annual Symposium on Foundations of Computer Science, US, Los Alamitos, IEEE Comp. Soc. Press, vol. Symp. 36, pp. 512-516 (Oct. 23, 1995) XP000557871.
20Amin Shokrollahi: "LDPC Codes: An Introduction" Internet Citation Apr. 2, 2003, XP002360065 Retrieved from the Internet: URL : http ://www . ipm. ac . ir/IPM/homepage/Amin 2. pdf [retrieved on Dec. 19, 2005].
21Amon P et al., "File Format for Scalable Video Coding", IEEE Transactions on Circuits and Systems for Video Technology, IEEE Service Center, Piscataway, NJ, US, vol. 17, No. 9, Sep. 1, 2007, pp. 1174-1185, XP011193013, ISSN: 1051-8215, DOI:10.1109/TCSVT.2007.905521.
22Anonymous: "Technologies under Consideration", 100. MPEG Meeting;Apr. 30, 2012-May 4, 2012; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1 /SC29/WG11) No. N12682, Jun. 7, 2012, XP030019156.
23Anonymous: "Technologies under Consideration", 98. MPEG Meeting; Nov. 28, 2011-Dec. 2, 2011; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11) No. N12330, Dec. 3, 2011, XP030018825.
24Anonymous: "Text of ISO/IEC 14496-12 3rd Edition", 83 MPEG Meeting; Jan. 14, 2008-Jan. 18, 2008; Antalya; (Motion Pictureexpert Group or ISO/IEC JTC1/SC29/WG11), No. N9678, Apr. 22, 2008, XP030016172.
25Anonymous: "Text of ISO/IEC 14496-15 2nd edition", 91 MPEG Meeting; Jan. 18, 2010-Jan. 22, 2010; Kyoto; (Motion Picture Expertgroup or ISO/IEC JTC1/SC29/WG11) No. N11139, Jan. 22, 2010, XP030017636.
26Anonymous: "Text of ISO/IEC IS 23009-1 Media Presentation Description and Segment Formats", 98. MPEG Meeting; Nov. 28, 2011-Dec. 2, 2012; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11),, No. N12329, Jan. 6, 2012, XP030018824.
27Anonymous: [Gruneberg, K., Narasimhan, S. and Chen, Y., editors] "Text of ISO/IEC 13818-1:2007/PDAM 6 MVC operation point descriptor", 90 MPEG Meeting; Oct. 26, 2009-Oct. 30, 2009; Xian; (Motion Picture Expertgroup or ISO/IEC JTC1/SC29/WG11|), No. N10942, Nov. 19, 2009, XP030017441.
28Atis: "PTV Content on Demand Service", IIF-WT-063R44, Nov. 11, 2010, pp. 1-124, XP055045168, Retrieved from the Internet: URL:ftp://vqeg.its.bldrdoc.gov/Documents/VQEG-Atlanta-Nov10/MeetingFiles/Liaison/IIF-WT-063R44-Content-on-Demand.pdf [retrieved on Nov. 22, 2012].
29Bar-Noy et al. "Efficient algorithms for optimal stream merging for media-on-demand," Draft (Aug. 2000), pp. 1-43.
30Bar-Noy, et al., "Competitive on-line stream merging algorithms for media-on-demand", Draft (Jul. 2000), pp. 1-34.
31Bigloo, A. et al.: "A Robust Rate-Adaptive Hybrid ARQ Scheme and Frequency Hopping for Multiple-Access Communication Systems," IEEE Journal on Selected Areas in Communications, US, IEEE Inc, New York (Jun. 1, 1994) pp. 889-893, XP000464977.
32Bitner, J.R., et al.: "Efficient Generation of the Binary Reflected Gray code and Its Applications," Communications of the ACM, pp. 517-521, vol. 19 (9), 1976.
33Blomer, et al., "An XOR-Based Erasure-Resilient Coding Scheme," ICSI Technical Report No. TR-95-048 (1995) [avail. at ftp://ftp.icsi.berkeley.edu/pub/techreports/1995/tr-95-048.pdf].
34Bouazizi I., et al., "Proposals for ALC/FLUTE server file format (14496-12Amd.2)", 77. MPEG Meeting; Jul. 17, 2006-Jul. 21, 2006; Klagenfurt; (Motion Pictureexpert Group or ISO/IEC JTC1/SC29/WG11), No. M13675, Jul. 12, 2006, XP030042344, ISSN: 0000-0236.
35Bross et al., "WD4: Working Draft 4 of High-Efficiency Video Coding," JCTVC-F803-d2, (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11 Joint Collaborative Team on Video Coding, 6th Meeting, Torino, IT, Jul. 14-22, 2011, 226 pages.
36Bross et al., "WD5: Working Draft 5 of High-Efficiency Video Coding," JCTVC-G1103-d2, (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11 Joint Collaborative Team on Video Coding, 7th Meeting, Geneva, Switzerland (Nov. 2011), 214 pages.
37Bross, et al., "High efficiency video coding (HEVC) text specification draft 6," JCTVC-H1003, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, 8th Meeting: San Jose, CA, USA, Feb. 1-10, 2012, 259 pp.
38Bross, et al., "High efficiency video coding (HEVC) text specification draft 6," Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11 JCTVC-H1003, 7th Meeting: Geneva, CH, Nov. 21-30, 2011, pp. 259.
39Bross, et al., "High efficiency video coding (HEVC) text specification draft 7," Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11 9th Meeting: Geneva, CH, Apr. 27-May 7, 2012, JCTVC-I1003-d21, pp. 290.
40Bross, et al., "High efficiency video coding (HEVC) text specification draft 8," Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11 10th Meeting: Stockholm, SE, Jul. 11-20, 2012, JCTVC-J1003-d7, pp. 261.
41Byers, J.W. et al.: "A Digital Fountain Approach to Reliable Distribution of Bulk Data," Computer Communication Review, Association for Computing Machinery. New York, US, vol. 28, No. 4 (Oct. 1998) pp. 56-67 XP000914424 ISSN:0146-4833.
42Byers, J.W. et al.: "Accessing multiple mirror sites in parallel: using Tornado codes to speed up downloads," 1999, Eighteenth Annual Joint Conference of the IEEE Corrupter and Communications Socities, pp. 275-283, Mar. 21, 1999, XP000868811.
43Cataldi et al., "Sliding-Window Raptor Codes for Efficient Scalable Wireless Video Broadcasting With Unequal Loss Protection", IEEE Transactions on Image Processing, Jun. 1, 2010, pp. 1491-1503, vol. 19, No. 6, IEEE Service Center, XP011328559, ISSN: 1057-7149, DOI: 10.1109/TIP.2010.2042985.
44Charles Lee L.H, "Error-Control Block Codes for Communications Engineers", 2000, Artech House, XP002642221 pp. 39-45.
45Chen et al., "Response to the CfP on HTTP Streaming: Adaptive Video Streaming based on AVC", 93. MPEG Meeting; Jul. 26, 2010-Jul. 30, 2010; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11), No. M17909, Jul. 26, 2010, XP030046499.
46Chikara S., et al., "Add-on Download Scheme for Multicast Content Distribution Using LT Codes", IEICE. B, Communications, Aug. 1, 2006, J89-B (8), pp. 1379-1389.
47Choi S: "Temporally enhanced erasure codes for reliable communication protocols" Computer Networks, Elsevier Science Publishers B.V., Amsterdam, NL, vol . 38, No. 6, Apr. 22, 2002, pp. 713-730, XP004345778, ISSN: 1389-1286, DOI:10.1016/S1389-1286(01)00280-8.
48Clark G.C., et al., "Error Correction Coding for Digital Communications, System Applications," Error Correction Coding for Digital Communications, New York, Plenum Press, US, Jan. 1, 1981, pp. 331-341.
49D. Gozalvez et,al. "AL-FEC for Improved Mobile Reception of MPEG-2 DVB-Transport Streams" Hindawi Publishing Corporation, International Journal of Digital Multimedia Broadcasting vol. 2009, Dec. 31, 2009, pp. 1-10, XP002582035 Retrieved from the Internet: URL:http://www.hindawi.com/journals/ijdmb/2009/614178.htnnl> [retrieved on May 12, 2010] .
50Dan, A. et al.: "Scheduling Policies for an On-Demand Video Server with Batching," Proc. ACM Multimedia, pp. 15-23 (Oct. 1998).
51Davey, M.C. et al.: "Low Density Parity Check Codes over GF(q)" IEEE Communications Letters, vol. 2, No. 6 pp. 165-167 (1998).
52Digital Fountain: "Raptor code specification for MBMS file download," 3GPP SA4 PSM AD-HOC #31 (May 21, 2004) XP002355055 pp. 1-6.
53Digital Fountain: "Specification Text for Raptor Forward Error Correction," TDOC S4-050249 of 3GPP TSG SA WG 4 Meeting #34 [Online] (Feb. 25, 2005) pp. 1-23, XP002425167, Retrieved from the Internet: URL:http://www.3gpp.org/ftp/tsg-sa/WG4-CODEC/TSGS4-34/Docs.
54DVB-IPI Standard: DVB BlueBook A086r4 (Mar. 2007) Transport of MPEG 2 Transport Streatm (TS) Based DVB Services over IP Based Networks, ETSI Technical Specification 102 034 v1.3.1.
55Eager, et al. "Minimizing bandwidth requirements for on-demand data delivery," Proceedings of the International Workshop on Advances in Multimedia Information Systems, p. 80-87 (Indian Wells, CA Oct. 1999).
56Eager, et al., "Optimal and efficient merging schedules for video-on-demand servers", Proc. ACM Multimedia, vol. 7, pp. 199-202 (1999).
57Esaki, et al.: "Reliable IP Multicast Communication Over ATM Networks Using Forward Error Correction Policy," IEICE Transactions on Communications, JP, Institute of Electronics Information and Comm. ENG. Tokyo, vol. E78-V, No. 12, (Dec. 1995), pp. 1622-1637, XP000556183.
58Feng, G., Error Correcting Codes over Z2m for Algorithm-Based Fault-Tolerance, IEEE Transactions on Computers, vol. 43, No. 3, Mar. 1994, pp. 370-374.
59Fernando, et al., "httpstreaming of MPEG Media-Response to CfP", 93 MPEG Meeting; Jul. 26, 2010-Jul. 30, 2010; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SCE29/WG11), No. M17756, Jul. 22, 2010, XP030046346.
60Fielding et al., "RFC 2616: Hypertext Transfer Protocol HTTP/1.1", Internet Citation, Jun. 1999 (Jun. 1999), pp. 165, XP002196143, Retrieved from the Internet: URL:http://www.rfc-editor-org/ [retrieved on Apr. 15, 2002].
61Frojdh P., et al., "Study on 14496-12:2005/PDAM2 ALU/ FLUTE Server File Format", 78.MPEG Meeting; Oct. 23, 2006-Oct. 27, 2006; Hangzhou: (Motion Picturexpert Group or ISO/ IEC JTC1/SC29/WG11) No. M13855, Oct. 13, 2006, XP030042523, ISSN: 0000-0233.
62Gao, L. et al.: "Efficient Schemes for Broadcasting Popular Videos," Proc. Inter. Workshop on Network and Operating System Support for Digital Audio and Video, pp. 1-13 (1998).
63Gasiba, Tiago et al., "System Design and Advanced Receiver Techniques for MBMS Broadcast Services" Proc. 2006 International Conference on Communications (ICC 2006), Jun. 1, 2006, pp. 5444-5450, XP031025781 ISBN: 978-1-4244-0354-7.
64Gemmell, et al., "A Scalable Multicast Architecture for One-To-Many Telepresentations", Multimedia Computing and Systems, 1998/Proceedings. IEEE International Conference on Austin, TX, USA Jun. 28-Jul. 1, 1998, Los Alamitos, CA USA, IEEE Comput. Soc, US, Jun. 28, 1998, pp. 128-139, XP010291559.
65Gerard F., et al., "HTTP Streaming MPEG media-Response to CFP", 93. MPEG Meeting, Geneva Jul. 26, 2010 to Jul. 30, 2010.
66Gil A., et al., "Personalized Multimedia Touristic Services for Hybrid Broadcast/Broadband Mobile Receivers," IEEE Transactions on Consumer Electronics, 2010, vol. 56 (1), pp. 211-219.
67Goyal: "Multiple Description Coding: Compression Meets the Network," In Signal Processing Magazine, IEEE, vol. 18., Issue 5 (Sep. 2001) pp. 74-93 URL:http://www.rle.mit.edu/stir/documents/Goyal-SigProcMag2001-MD.pdf [Nov. 4, 2007].
68Gozalvez D et, al: "Mobile reception of DVB-T services by means of AL-FEC protection" Proc. IEEE Intern. Symposium on Broadband Multimedia Systems and Broadcasting (BMSB '09), IEEE, Piscataway, NJ, USA, May 13, 2009, pp. 1-5, XP031480155 ISBN: 978-1-4244-2590-7.
69Gracie et al., "Turbo and Turbo-Like Codes: Principles and Applications in Telecommunications", Proceedings of the IEEE, Jun. 1, 2007, pp. 1228-1254, vol. 95, No. 6, IEEE, XP011189323, ISSN: 0018-9219, DOI: 10.1109/JPR0C.2007.895197.
70Hagenauer, J. : "Soft is better than hard" Communications, Coding and Cryptology, Kluwer Publication May 1994, XP002606615 Retrieved from the Internet : URL: http://www. Int . ei .turn. de/veroeffentlic hungen/1994/ccc94h. pdf [retrieved on Oct. 25, 2010].
71Hannuksela M.M., et al., "DASH: Indication of Subsegments Starting with SAP", 97. MPEG Meeting; Jul. 18, 2011-Jul. 22, 2011; Torino; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11) No. m21096, Jul. 21, 2011, XP030049659.
72Hannuksela M.M., et al., "ISOBMFF: SAP definitions and 'sidx' box", 97. MPEG Meeting; Jul. 18, 2011-Jul. 22, 2011; Torino; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11) No. m21435, Jul. 22, 2011, XP030049998.
73Hasan M A., et al., "Architecture for a Low Complexity Rate-Adaptive Reed-Solomon Encoder", IEEE Transactions on Computers, IEEE Service Center, Los Alamitos, CA, US, vol. 44, No. 7, Jul. 1, 1995, pp. 938-942, XP000525729, ISSN: 0018-9340, DOI: 10.1109/12.392853.
74Hershey, et al., "Random Parity Coding (RPC)", 1996 IEEE International Conference on Communications (ICC). Converging Technologies for Tomorrow's Applications. Dallas, Jun. 23-27, 1996, IEEE International Conference on Communications (ICC), New York, IEEE, US, vol. 1, Jun. 23, 1996, pp. 122-126, XP000625654.
75Hua, et al., "Skyscraper broadcasting: A new broadcsting system for metropolitan video-on-demand systems", Proc. ACM SIGCOMM, pp. 89-100 (Cannes, France, 1997).
76Huawei et al., "Implict mapping between CCE and PUCCH for ACK/NACK TDD", 3GPP Draft; R1-082359, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, vol. RAN WG1, no. Warsaw, Poland, Jun. 24, 2008, XP050110650, [retrieved on Jun. 24, 2008] .
77IETF RFC 2733: Rosenberg, J. et al. "An RTP Payload Format for Generic Forward Error Correction," Network Working Group, RFC 2733 (Dec. 1999).
78International Search Report and Written Opinion-PCT/US2012/024737-ISA/EPO-May 11, 2012.
79International Search Report and Written Opinion-PCT/US2012/024755-ISAEPO-Apr. 23, 2012.
80International Standard ISO/IEC 14496-12, Information Technology-Coding of audio-visual objects-Part 12: ISO base media file format, Third Edition, Oct. 15, 2008, 120 pp.
81ISO/IEC JTC 1/SC 29, ISO/IEC FCD 23001-6, Information technology-MPEG systems technologies-Part 6: Dynamic adaptive streaming over HTTP (DASH), Jan. 28, 2011.
82ITU-T H.264, Series H: Audiovisual and Multimedia Systems, Infrastructure of audiovisual services-Coding of moving video, Advanced video coding for generic audiovisual services, The International Telecommunication Union. Jun. 2011, 674 pp.
83Jiang., File Format for Scalable Video Coding, PowerPoint Presentation for CMPT 820, Summer 2008.
84Jin Li, "The Efficient Implementation of Reed-Solomon High Rate Erasure Resilient Codes" Proc. 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, Philadelphia, PA, USA, IEEE, Piscataway, NJ, vol . 3, Mar. 18, 2005, pp. 1097-1100, XP010792442, DOI: 10.1109/ICASSP.2005.1415905 ISBN: 978-0-7803-8874-1.
85Juhn, L. et al.: "Adaptive Fast Data Broadcasting Scheme for Video-on-Demand Service," IEEE Transactions on Broadcasting, vol. 44, No. 2, pp. 182-185 (Jun. 1998).
86Juhn, L. et al.: "Harmonic Broadcasting for Video-on-Demand Service," IEEE Transactions on Broadcasting, vol. 43, No. 3, pp. 268-271 (Sep. 1997).
87Kallel, "Complementary Punctured Convolutional (CPC) Codes and Their Applications", IEEE Transactions on Communications, IEEE Inc., New York, US, Vol. 43, No. 6, Jun. 1, 1995, pp. 2005-2009.
88Kim J., et al., "Enhanced Adaptive Modulation and Coding Schemes Based on Multiple Channel Reportings for Wireless Multicast Systems", 62nd IEEE Vehicular Technology Conference, VTC-2005-FALL, Sep. 25-28, 2005, vol. 2, pp. 725-729, XP010878578, DOI: 1 0.11 09/VETECF.2005.1558019, ISBN: 978-0-7803-9152-9.
89Kimata H et al., "Inter-View Prediction With Downsampled Reference Pictures", ITU Study Group 16-Video Coding Experts Group-ISO/IEC MPEG & ITU-T VCEG(ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q6), No. JVT-W079, Apr. 19, 2007, XP030007039.
90Kimura et al., "A Highly Mobile SDM-0FDM System Using Reduced-Complexity-and-Processing", IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Sep. 1, 2007, pp. 1-5, IEEE, XP031168836, ISBN: 978-1-4244-1143-6, DOI: 10.1109/PIMRC.2007.4394758.
91Kozamernik F: "Media streaming over the Internet", Internet Citation, Oct. 2002, XP002266291, Retrieved from the Internet: URL: http://www.ebu.ch/trev-292-kozamerni k. pdf [retrieved on Jan. 8, 2004] section "Video codecs for scalable streaming".
92Lee L., et al.,"VLSI implementation for low density parity check decoder", Proceedings of the 8th IEEE International Conference on Elecctronics, Circuits and Systems, 2001. ICECS 2001, Sep. 2, 2001, vol. 3, pp. 1223-1226.
93Lee, J.Y., "Description of Evaluation Experiments on ISO/IEC 23001-6, Dynamic Adaptive Streaming over HTTP", ISO/IEC JTC1/SC29/WG11MPEG2010/N11450, Jul. 31, 2010, 16 pp.
94Li, M., et al., "Playout Buffer and Rate Optimization for Streaming over IEEE 802.11 Wireless Networks", Aug. 2009, Worcester Polytechnic Institute, USA.
95Lin, S. et al.: "Error Control Coding-Fundamentals and Applications," 1983, Englewood Cliffs, pp. 288, XP002305226.
96Luby Digital Fountain A Shokrollahi Epfl M Watson Digital Fountain T Stockhammer Nomor Research M: "Raptor Forward Error Correction Scheme for Object Delivery; rfc5053.txt", IETF Standard, Internet Engineering Task Force, IETF, CH, Oct. 1, 2007, XP015055125, ISSN: 0000-0003.
97Luby et al., "Improved Low-Density Parity-Check Codes Using Irregular Graphs and Belief Propogation", Information Theory, 1998. Proceedings. 1998 IEEE International Symposium on Cambridge, MA, USA Aug. 16-21, 1998, pp. 1-9, New York, NY, USA, IEEE, US Aug. 16, 199.
98Luby et al., RaptorQ Forward Error Correction Scheme for Object Delivery draft-ietf-rmt-bb-fec-raptorq-00, Qualcomm, Inc. Jan. 28, 2010.
99Luby et, al. "Layered Coding Transport (LCT) Building Block", IETF RFC 5651, pp. 1-42, (Oct. 2009).
100Luby M et al: "IPTV Systems, Standards and Architectures: Part II-Application Layer FEC in IPTV Services" IEEE Communications Magazine, IEEE Service Center, Piscataway, US LNKDDOI: 10.1109/MCOM.2008.4511656, vol. 46, No. 5, May 1, 2008, pp. 94-101, XP011226858 ISSN: 0163-6804.
101Luby M. et al., "RaptorQ Forward Error Correction Scheme for Object Delivery", IETF draft ietf-rmt-bb-fec-raptorq-04, Reliable Multicast Transport, Internet Engineering Task Force (IETF), Standard Workingdraft, Internet Society (ISOC), Aug. 24, 2010, pp. 1-68, XP015070705, [retrieved on Aug. 24, 2010].
102Luby M., "LT Codes", Foundations of Computer Science, 2002, Proceedings, The 43rd Annual IEEE Symposium on, 2002.
103Luby M., "Simple Forward Error Correction (FEC) Schemes," draft-luby-rmt-bb-fec-supp-simple-00.txt, pp. 1-14, Jun. 2004.
104Luby Qualcomm Incorporated, "Universal Object Delivery using RaptorQ; draft-luby-uod-raptorq-OO.txt", Internet Engineering Task Force (IETF), Standardworkingdraft, Internet Society (ISOC), Mar. 7, 2011, pp. 1-10, XP015074424, [retrieved on Mar. 7, 2011] .
105Luby, et al., "Analysis of Low Density Codes and Improved Designs Using Irregular Graphs", 1998, Proceedings of the 30th Annual ACM Symposium on Theory of Computing, May 23, 1998, pp. 249-258, XP000970907.
106Luby, et al., "FLUTE-File Delivery over Unidirectional Transport", IETF RFC 3926, pp. 1-35, (Oct. 2004).
107Luby, et al.: "Analysis of Low Density Codes and Improved Designs Using Irregular Graphs," International Computer Science Institute Technical Report TR-97-045 (Nov. 1997) [available at ftp://ftp.icsi.berkeley.edu/pub/techreports/1997/tr-97-045.pdf].
108Luby, M. et al., "Practical Loss-Resilient Codes: Tornado Codes," 29th Annual ACM Symposium on Theory of Computing, vol. SYMP. 29, May 4, 1997, pp. 150-159, XP002271229.
109Luby, M. et al.: "Efficient Erasure Correction Codes," 2001, IEEE Transactions on Information Theory, Vo. 47, No. 2, pp. 569-584, XP002305225.
110Luby, M. et al.: "Pairwise Independence and Derandomization," Foundations and Trends in Theoretical Computer Science, vol. 1, Issue 4, 2005, Print ISSN 1551-305X, Online ISSN 1551-3068.
111Luby, M., et al., "Raptor Forward Error Correction Scheme for Object Delivery", IETF RFC5053, pp. 1-46 (Sep. 2007).
112Luby, M., et al., "Request for Comments: 3453: The Use of Forward Error Correction (FEC) in Reliable Multicast," Internet Article, [Online] Dec. 2002, pp. 1-19.
113Luby, M., et, al. "Forward Error Correction (FEC) Building Block", IETF RFC 5052, pp. 1-31, (Aug. 2007).
114Luby, Michael G. "Analysis of Random Processes via and-or Tree Evaluation," Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms,TR-97-0, 1998, pp. 364-373, (search date: Jan. 25, 2010) URL: .
115Luby, Michael G. "Analysis of Random Processes via and-or Tree Evaluation," Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms,TR-97-0, 1998, pp. 364-373, (search date: Jan. 25, 2010) URL: <http://portal.acm.prg.citation.cfm″id=314722>.
116MacKay, "Fountain codes Capacity approaching codes design and implementation", IEE Proceedings: Communications, Dec. 9, 2005, pp. 1062-1068, vol. 152, No. 6, Institution of Electrical Engineers, XP006025749, ISSN: 1350-2425, DOI: 10.1049/IP-C0M:20050237.
117Makoto N., et al., "On Tuning of Blocking LU decomposition for VP2000 series" The 42th Information Processing Society of Japan Conference (1st term in 1991), Feb. 25, 1991, pp. 71-72, 4B-8B.
118Mandelbaum D.M., "An Adaptive-Feedback Coding Scheme Using Incremental Redundancy", IEEE Trans on Information Theory, vol. May 1974, May 1974, pp. 388-389, XP002628271, the whole document.
119Matsuoka H., et al., "Low-Density Parity-Check Code Extensions Applied for Broadcast-Communication Integrated Content Delivery", Research Laboratories, NTT DOCOMO, Inc., 3-6, Hikari-No-Oka, Yokosuka, Kanagawa, 239-8536, Japan, ITC-SS21, 2010 IEICE, pp. 59-63.
120Michael G et al., "Improved low-density parity-check codes using irregular graphs", Information Theory, IEEE Transactions on,Feb. 2001,vol. 47, No. 2,pp. 585-598.
121Miller G., et al., "Bounds on the maximum likelihood decoding error probability of low density parity check codes", Information Theory, 2000. Proceedings. IEEE International Symposium on, 2000, p. 290.
122Mimnaugh, A et, al. "Enabling Mobile Coverage for DVB-T" Digital Fountain Whitepaper Jan. 29, 2008, pp. 1-9, XP002581808 Retrieved from the Internet: URL:http://www.digitalfountain.com/ufiles/ library/DVB-T-whitepaper.pdf> [retrieved on May 10, 2010].
123Min-Goo Kim: "On systematic punctured convolutional codes", IEEE Trans on Communications, vol. 45, No. 2, Feb. 1997, XP002628272, the whole document, pp. 133-139.
124Morioka S., "A Verification Methodology for Error Correction Circuits over Galois Fields", Tokyo Research Laboratory, IBM Japan Ltd, pp. 275-280, Apr. 22-23, 2002.
125Moriyama, S., "5. Present Situation of Terrestrial Digital Broadcasting in Europe and USA", Journal of the Institute of Image Information and Television Engineers, Nov. 20, 1999, vol. 53, No. 11, pp. 1476-1478.
126Motorola et al: "An Analysis of DCD Channel Mapping to BCAST File Delivery Sessions; OMA-CD-DCD-2007-0112-INP-DCD-Channel-Mapping-to-BCAST-Fi1e-Delivery", OMA-CD-DCD-2007-0112-INP-DCD-Channel-Mapping-to-BCAST-File-Delivery, Open Mobile Alliance (OMA), 4330 La Jolla Village Dr., Suite 110 San Diego, CA 92122; USA Oct. 2, 2007, pp. 1-13, XP064036903.
127Muller, et al., "A test-bed for the dynamic adaptive streaming over HTTP featuring session mobility" MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems, Feb. 23-25, 2011, San Jose, CA, pp. 271-276.
128Muramatsu J., et al., "Low density parity check matrices for coding of multiple access networks", Information Theory Workshop, 2003. Proceedings. 2003 IEEE , Apr. 4, 2003, pp. 304-307.
129Naguib, Ayman, et al., "Applications of Space-Time Block Codes and Interference Suppression for High Capacity and High Data Rate Wireless Systems," IEEE, 1998, pp. 1803-1810.
130Narayanan, et al., "Physical Layer Design for Packet Data Over IS-136", Vehicular Technology Conference, 1997, IEEE 47th Phoenix, AZ, USA May 4-7, 1997, New York, NY, USA, IEEE, US May 4, 1997, pp. 1029-1033.
131Nokia Corp., "Usage of 'mfra' box for Random Access and Seeking," S4-AHI127, 3GPP TSG-SA4 Ad-Hoc Meeting, Dec. 14-16, 2009, Paris, FR, 2 pp.
132Nokia: "Reed-Solomon Code Specification for. MBMS Download and Streaming Services", 3GPP Draft; 54-050265-RS-SPEC, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, vol. SA WG4, no. San Diego, USA; 20050415, Apr. 15, 2005, XP050287675, [retrieved on Apr. 15, 2005].
133Nonnenmacher, et al., "Parity-Based Loss Recovery for Reliable Multicast Transmission", IEEE / ACM Transactions on Networking, IEEE Inc. New York, US, Vol. 6, No. 4, Aug. 1, 1998, pp. 349-361.
134Ohashi A et al., "Low-Density Parity-Check (LDPC) Decoding of Quantized Data," Technical Report of the Institute of Electronics, Information and Communication Engineers, Aug. 23, 2002, vol. 102, No. 282, pp. 47-52, RCS2002-154.
135Ozden, B. et al.: "A Low-Cost Storage Service for Movie on Demand Databases," Proceedings of the 20th Very Large DataBases (VLDB) Conference, Santiago, Chile (1994).
136PA. Chou, A. Mohr, A. Wang, S. Mehrotra, "FEC and Pseudo-ARQ for Receiver-Driven Layered Multicast of Audio and Video," pp. 440-449, IEEE Computer Society, Data Compression Conference (2000).
137Pantos R et al., "HTTP Live Streaming; draft-pantos-http-1ive-streaming-OT.txt ", HTTP Live Streaming; Draft-Pant0s-HTTP-Live-Streaming-01.txt, Internet Engineering Task Force, IETF; Standardworkingdraft, Internet Society (ISOC) 4, Rue Des Falaises CH-1205 Geneva, Switzerland, No. 1, Jun. 8, 2009, XP015062692.
138Pantos, "HTTP Live Streaming draft-pantos-http-live-streaming-02", Informational, Internet-Draft, Intended status: Informational, Expires: Apr. 8, 2010, http://tools.ietf.org/html/draft-pantos-http-live-streaming-02, pp. 1-20, Oct. 5, 2009.
139Paris, et al., "A low bandwidth broadcasting protocol for video on demand", Proc. International Conference on Computer Communications and Networks, vol. 7, pp. 690-697 (Oct. 1998).
140Paris, et al., "Efficient broadcasting protocols for video on demand", International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication systems (MASCOTS), vol. 6, pp. 127-132 (Jul. 1998).
141Perkins, et al.: "Survey of Packet Loss Recovery Techniques for Streaming Audio," IEEE Network; Sep./Oct. 1998, pp. 40-48.
142Petition decision for Petition Under 37 C.F.R. 1.78 to Accept an Unintentionally Delayed Priority Claim under 35 U.S.C. 120 in U.S. Patent No. 7,532,132, dated Jul. 21, 2011, 2 pages.
143Petition under 37 C.F.R. 1.78 to Accept an Unintentionally Delayed Priority Claim under 35 U.S.C. 120 in U.S. Patent No. 7,532,132, dated May 27, 2011, 2 pages.
144Plank J. S., "A Tutorial on Reed-Solomon Coding for Fault-Tolerance I N Raid-Like Systems", Software Practice & Experience, Wiley & Sons, Bognor Regis, GB, vol. 27, No. 9, Sep. 1, 1997, pp. 995-1012, XP00069594.
145Pless and WC Huffman EDS V S: Algebraic geometry codes, Handbook of Coding Theory, 1998, pp. 871-961, XP002300927.
146Pursley, et al.: "Variable-Rate Coding for Meteor-Burst Communications," IEEE Transactions on Communications, US, IEEE Inc. New York (1989) vol. 37, No. 11, pp. 1105-1112 XP000074533.
147Pursley, M. et al.: "A Correction and an Addendum for Variable-Rate Coding for Meteor-Burst Communications," IEEE Transactions on Communications, vol. 43, No. 12 pp. 2866-2867 (Dec. 1995).
148Pyle, et al., "Microsoft http smooth Streaming: Microsoft response to the Call for Proposal on httpstreaming", 93 MPEG Meeting; Jul. 26, 2010-Jul. 30, 2010; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SCE29/WG11), No. M17902, Jul. 22, 2010, XP030046492.
149Qualcomm Europe S A R L: "Baseline Architecture and Definitions for HTTP Streaming", 3GPP Draft; S4-090603-HTTP-Streaming-Architecture, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, no. Kista; 20090812, Aug. 12, 2009, XP050356889.
150Qualcomm Incorporated: "Adaptive HTTP Streaming: Complete Proposal", 3GPP TSG-SA4 AHI Meeting S4-AHI170, Mar. 2, 2010, URL, http://www.3gpp.org/FTP/tsg-sa/WG4-CODEC/Ad-hoc-MBS/Docs-AHI/S4-AHI170.zip, S4-AH170-CR-AdaptiveHTTPStreaming-Full.doc.
151Qualcomm Incorporated: "Corrections to 3GPP Adaptive HTTP Streaming", 3GPP TSG-SA4 #59 Change Request 26.234 CR0172 S4-100403, Jun. 16, 2010, URL, http://www.3gpp.org/FTP/tsg-sa/WG4-CODEC/TSGS4-59/Docs/54-100403.zip, S4-100403-CR-26234-0172-AdaptiveHTTPStreaming-Re1-9.doc.
152Qualcomm Incorporated: "RatorQ Forward Error Correction Scheme for Object Delivery draft-ietf-rmt-bb-fec-raptor-04", Internet Engineering Task Force, IETF, pp. 1-68, Aug. 24, 2010.
153Qualcomm Incorporated: "Use Cases and Examples for Adaptive httpstreaming", 3GPP Draft; S4-100408-USECASES-HSD, 3rd Generation Partnership Project (JGPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, vol. SA WG4, no. Prague, Czech Republic; 20100621, Jun. 17, 2010, XP050438085, [retrieved on Jun. 17, 2010].
154Ramsey B, "HTTP Status: 206 Partial Content and Range Requests," May 5, 2008 obtained at http://benramsey.com/blog/2008/05/206-partial-content-and-range-requests/.
155Rangan, et al., "Designing an On-Demand Multimedia Service," IEEE Communication Magazine, vol. 30, pp. 56-64, (Jul. 1992).
156Realnetworks Inc et al., "Format for HTTP Streaming Media Presentation Description", 3GPP Draft; S4-100020, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Anti Polis Cedex; France, vol. SA WG4, no. St Julians, Malta; 20100125, Jan. 20, 2010, XP050437753, [retrieved on Jan. 20, 2010].
157Research in Motion UK Limited: "An MPD delta file for httpstreaming", 3GPP Draft; S4-100453, 3rd Generation Partnership Project (SGPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, vol. SA WG4, no. Prague, Czech Republic; 20100621, Jun. 16, 2010, XP050438066, [retrieved on Jun. 16, 2010].
158Rhyu, et al., "Response to Call for Proposals on httpstreaming of MPEG Media", 93 MPEG Meeting; Jul. 26, 2010-Jul. 30, 2010; Geneva; (Motion Picture Expert Group or ISO/IEC JTC1/SCE29/WG11) No. M17779, Jul. 26, 2010, XP030046369.
159Rizzo, L. "Effective Erasure Codes for Reliable Computer Communication Protocols," Computer Communication Review, 27 (2) pp. 24-36 (Apr. 1, 1997), XP000696916.
160Roca, V. et al.: "Design, Evaluation and Comparison of Four Large Block FEC Codecs, LDPC, LDGM, LDGM Staircase and LDGM Triangle, plus a Reed-Solomon Small Block FEC Codec," INRIA Research Report RR-5225 (2004).
161Roca, V., et, al. "Low Density Parity Check (LDPC) Staircase and Triangle Forward Error Correction (FEC) Schemes", IETF RFC 5170 (Jun. 2008), pp. 1-34.
162Rost, S. et al., "The Cyclone Server Architecture: streamlining delivery of popular content," 2002, Computer Communications, vol. 25, No. 4, pp. 1-10.
163Roth, R., "On MDS Codes via Cauchy Matrices", IEEE Transactions on Information Theory, vol. 35, No. 6, Nov. 1989, pp. 1314-1319.
164Roth, R., et al., "A Construction of Non-Reed-Solomon Type MDS Codes", IEEE Transactions of Information Theory, vol. 35, No. 3, May 1989, pp. 655-657.
165Roumy A., et al., "Unequal Erasure Protection and Object Bundle Protection with the Generalized Object Encoding Approach", Inria-00612583, Version 1, Jul. 29 2011, 25 pages.
166Samukawa, H. "Blocked Algorithm for LU Decomposition" Journal of the Information Processing Society of Japan, Mar. 15, 1993, vol. 34, No. 3, pp. 398-408.
167Schulzrinne, et al., "Real Time Streaming Protocol (RTSP)" Network Working Group, Request for Comments: 2326, Apr. 1998, pp. 1-92.
168Seshan, S. et al., "Handoffs in Cellular Wireless Networks: The Daedalus Implementation and Experience," Wireless Personal Communications, NL; Kluwer Academic Publishers, vol. 4, No. 2 (Mar. 1, 1997) pp. 141-162, XP000728589.
169Shacham: "Packet Recovery and Error Correction in High-Speed Wide-Area Networks," Proceedings of the Military Communications Conference. (Milcom), US, New York, IEEE, vol. 1, pp. 551-557 (1989) XP000131876.
170Shierl T; Gruneberg K; Narasimhan S; Vetro A: "ISO/IEC 13818-1:2007/FPDAM 4-Information Technology Generic Coding of Moving Pictures and Audio Systems amendment 4: Transport of Multiview Video over ITU-T Rec H.222.0 ISO/IEC 13818-1" ITU-T REC. H.222.0(May 2006)FPDAM 4, vol. MPEG2009, No. 10572, May 11, 2009, pp. 1-20, XP002605067 p. 11, last two paragraphs sections 2.6.78 and 2.6.79 table T-1.
171Shokrollahi et al., "Design of Efficient Easure Codes with Differential Evolution", IEEE International Symposium on Information Theory, Jun. 25, 2000, pp. 5-5.
172Shokrollahi, A.: "Raptor Codes," Internet Citation [Online] (Jan. 13, 2004) XP002367883, Retrieved from the Internet: URL:http://www.cs.huji.ac.il/labs/danss/p2p/resources/raptor.pdf.
173Shokrollahi, Amin. "Raptor Codes," IEEE Transactions on Information Theory, Jun. 2006, vol. 52, No. 6, pp. 2551-2567, (search date: Feb. 1, 2010) URL: <http://portal.acm.org/citation.cfm″id=1148681> .
174Sincoskie, W. D., "System Architecture for Large Scale Video on Demand Service," Computer Network and ISDN Systems, pp. 155-162, (1991).
175Stockhammer T., et al., "DASH: Improvements on Representation Access Points and related flags", 97. MPEG Meeting; Jul. 18, 2011-Jul. 22, 2011; Torino; (Motion Picture Expert Group or ISO/IEC JTC1/SC29/WG11) No. m20339, Jul. 24, 2011, XP030048903.
176Stockhammer, "WD 0.1 of 23001-6 Dynamic Adaptive Streaming over HTTP (DASH)", MPEG-4 Systems, International Organisation for Standardisation, ISO/IEC JTC1/SC29/WG11, Coding of Moving Pictures and Audio, MPEG 2010 Geneva/m11398, Jan. 6, 2011, 16 pp.
177Sullivan et al., Document: JVT-AA007, "Editors' Draft Revision to ITU-T Rec. H.264|ISO/IEC 14496-10 Advanced Video Coding-in Preparation for ITU-T SG 16 AAP Consent (in integrated form)," Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6), 30th Meeting: Geneva, CH, Jan. 29-Feb. 3, 2009, pp. 1-683, http://wftp3.itu.int/av-arch/jvt-site/2009-01-Geneva/JVT-AD007.zip.
178Sun, et al., "Seamless Switching of Scalable Video Bitstreams for Efficient Streaming," IEEE Transactions on Multimedia, vol. 6, No. 2, Apr. 2004, pp. 291-303.
179Telefon AB LM Ericsson, et al., "Media Presentation Description in httpstreaming", 3GPP Draft; S4-100080-MPD, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, vol. SA WG4, no. St Julians, Malta; 20100125, Jan. 20, 2010, XP050437773, [retrieved on Jan. 20, 2010].
180Tetsuo M., et al., "Comparison of Loss Resilient Ability between Multi-Stage and Reed-Solomon Coding ", Technical report of IEICE. CQ, Communication Quality, vol. 103 (178), Jul. 4, 2003, pp. 19-24. 1:811.
181Thomas Wiegand et al.,"WD1: Working Draft 1 of High-Efficiency Video Coding", JCTVC-C403, Joint Collaborative Team on Video Coding (JCT-VC), of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, 3rd Meeting: Guangzhou, CN, Oct. 7-15, 2010.
182Todd, "Error Correction Coding: Mathematical Methods and Algorithms", Mathematical Methods and Algorithms, Jan. 1, 2005, pp. 451-534, Wiley, XP002618913.
183Tsunoda T., et al., "Reliable Streaming Contents Delivery by Using Multiple Paths," Technical Report of the Institute of Electronics, Information and Communication Engineers, Japan, Mar. 2004, vol. 103, No. 692, pp. 187-190, NS2003-331, IN2003-286.
184U.S. Appl. No. 12/840,146, by Ying Chen et al., filed Jul. 20, 2010.
185U.S. Appl. No. 12/908,537, by Ying Chen et al., filed Oct. 20, 2010.
186U.S. Appl. No. 12/908,593, by Ying Chen et al., filed Oct. 20, 2010.
187U.S. Appl. No. 13/082,051, by Ying Chen et al., filed Apr. 7, 2011.
188U.S. Appl. No. 13/205,559, by Ying Chen et al., filed Aug. 8, 2011.
189U.S. Appl. No. 13/205,565, by Ying Chen et al., filed Aug. 8, 2011.
190U.S. Appl. No. 13/205,574, by Ying Chen et al., filed Aug. 8, 2011.
191Universal Mobile Telecommunications System (UMTS); LTE; Transparent end-to-end Packet-switched Streaming Service (PSS); Protocols and codecs (3GPP TS 26.234 version 9.3.0 Release 9), Technical Specification, European Telecommunications Standards Institute (ETSI), 650, Route Des Lucioles; F-06921 Sophia-Antipolis; France, vol. 3GPP SA, No. V9.3.0, Jun. 1, 2010, XP014047290, paragraphs [5.5.4.2], [5.5.4.3], [5.5.4.4], [5.4.5], [5.5.4.6] paragraphs [10.2.3], [11.2.7], [12.2.3], [12.4.2], [12.6.2] paragraphs [12.6.3], [12.6.3.1], [12.6.4], [12.6.6].
192Viswanathan, et al., "Metropolitan area video-on-demand services using pyramid broadcasting", Multimedia Systems, 4(4): 197-208 (1996).
193Viswanathan, et al., "Pyramid Broadcasting for Video-on-Demand Service", Proceedings of the SPIE Multimedia Computing and Networking Conference, vol. 2417, pp. 66-77 (San Jose, CA, Feb. 1995).
194Viswanathan,Subramaniyam R., "Publishing in Wireless and Wireline Environments," Ph. D Thesis, Rutgers, The State University of New Jersey (Nov. 1994), 180pages.
195Wadayama T, "Introduction to Low Density Parity Check Codes and Sum-Product Algorithm," Technical Report of the Institute of Electronics, Information and Communication Engineers, Dec. 6, 2001, vol. 101, No. 498, pp. 39-46, MR2001-83.
196Watson M., et al., "Forward Error Correction (FEC) Framework draft-ietf-fecframe-framework-11," 2011, pp. 1-38, URL,http://tools.ietf.org/pdf/draft-ietf-fecframe-framework-11.pdf.
197Watson M., et al., "Raptor FEC Schemes for FECFRAME draft-ietf-fecframe-raptor-04," 2010, pp. 1-21, URL,http://tools.ietf.org/pdf/draft-ietf-fecframe-raptor-04.pdf.
198Watson, M., et, al. "Asynchronous Layered Coding (ALC) Protocol Instantiation", IETF RFC 5775, pp. 1-23, (Apr. 2010).
199Wiegand et al., "WD3: Working Draft 3 of High-Efficiency Video Coding," Document JCTVC-E603, 5th Meeting: Geneva, CH, Mar. 16-23, 2011,193 pp.
200Wiegand T. et al., "WD2: Working Draft 2 of High-Efficiency Video Coding", 20110128, No. JCTVC-D503, Jan. 28, 2011, XP002679642, Retrieved from the Internet: URL: http://wftp3.itu.int/av-arch/jctvc-site/2011-01-D-Daegu/ [retrieved on Jul. 11, 2012].
201Wong, J.W., "Broadcast delivery", Proceedings of the IEEE, 76(12): 1566-1577, (1988).
202Yamanouchi N., et al., "Internet Multimedia Transmission with Packet by Using Forward Error Correction," Proceedings of DPS Workshop, the Information Processing Society of Japan, Dec. 6, 2000, vol. 2000, No. 15, pp. 145-150.
203Yamauchi, Nagamasa. "Application of Lost Packet Recovery by Front Error Correction to Internet Multimedia Transfer" Proceedings of Workshop for Multimedia Communication and Distributed Processing, Japan, Information Processing Society of Japan (IPS), Dec. 6, 2000, vol. 2000, No. 15, pp. 145-150.
204Yamazaki M., et al., "Multilevel Block Modulation Codes Construction of Generalized DFT," Technical Report of the Institute of Electronics, Information and Communication Engineers, Jan. 24, 1997, vol. 96, No. 494, pp. 19-24, IT96-50.
205Yin et al., "Modified Belief-Propogation algorithm for Decoding of Irregular Low-Density Parity-Check Codes", Electronics Letters, IEE Stevenage, GB, vol. 38, No. 24, Nov. 21, 2002, pp. 1551-1553.
206Zorzi, et al.: "On the Statistics of Block Errors in Bursty Channels," IEEE Transactions on Communications, vol. 45, No. 6, Jun. 1997, pp. 660-667.
Referenced by
Citing PatentFiling datePublication dateApplicantTitle
US9438669 *19 Jan 20126 Sep 2016Naver CorporationSystem and method for packetizing data stream in peer-to-peer (P2P) based streaming service
US973623619 Jan 201215 Aug 2017Naver CorporationSystem and method for managing buffering in peer-to-peer (P2P) based streaming service and system for distributing application for processing buffering in client
US20130018991 *19 Jan 201217 Jan 2013Nhn Business Platform CorporationSystem and method for packetizing data stream in peer-to-peer (p2p) based streaming service
Classifications
International ClassificationH03M13/00, H04L1/00, H03M13/37
Cooperative ClassificationH04L1/007, H03M13/3761, H04L1/0057, H04L1/0083, H04L1/0086, H04L1/0042
Legal Events
DateCodeEventDescription
6 Apr 2012ASAssignment
Owner name: QUALCOMM INCORPORATED, CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LUBY, MICHAEL G.;PAKZAD, PAYAM;SHOKROLLAHI, MOHAMMAD AMIN;AND OTHERS;SIGNING DATES FROM 20110427 TO 20120203;REEL/FRAME:028007/0223