WO2003075471A2

WO2003075471A2 - System and method for joint maximal ratio combining

Info

Publication number: WO2003075471A2
Application number: PCT/US2003/005647
Authority: WO
Inventors: Yohannes Tesfai; Chandra Vaidyanathan; Gary L. Sugar
Original assignee: Cognio, Inc.
Priority date: 2002-03-01
Filing date: 2003-02-26
Publication date: 2003-09-12
Also published as: TW200304734A; EP1769585A2; TWI226765B; WO2003075471A3; US7573945B2; US20040136466A1; US20090296848A1; AU2003219882A8; AU2003219882A1; EP1769585A4

Abstract

A spatial signal processing system and method are provided to optimize the received signal-to-noise ratio (SNR) at a first radio communication device (100) based on the transmit filter at another radio communication (200). Using an estimate of the channel derived from a signal received at one device from another device, an iterative process is provided to determine complex weights for one or more tapped delay-line transmit filters at each of two communication devices that optimize the received SNR.

Description

SYSTEM AND METHOD FOR JOINT MAXIMAL RATIO COMBINING USING TIME-DOMAIN BASED SIGNAL PROCESSING

This application claims priority to U.S. Provisional Application No. 60/361,055, filed March 1, 2002, and to U.S. Provisional Application No. 60/380,139, filed May 6, 2002, the entirety of both of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION The present invention is directed to a joint temporal and spatial antenna processing scheme useful in wireless communication applications, such as short- range wireless applications.

Antenna diversity schemes are well known techniques to improve the performance of radio frequency (RF) communication between two RF devices. Types of antenna diversity schemes include antenna selection diversity and maximal ratio combining, hi an antenna selection diversity scheme, a radio communication device selects one of N (e.g., two) antennas for transmission to a particular communication device based on which of its N antennas best received a signal from that radio communication device. On the other hand, maximal ratio combining schemes involve scaling the signal to be transmitted with a complex antenna weight associated with a corresponding one of a plurality of antennas. A signal received by a plurality of antennas can also be weighted by a plurality of complex receive antenna weights. Selection of the antenna weights to optimize communication between two communication devices determines the performance of maximal ratio combining schemes.

A joint maximal ratio combining antenna processing technique is one in which a first communication device, having a plurality of antennas, weights a signal to be transmitted by its antennas to a second communication device also having a plurality of antennas. The second communication device weights and combines the received signals received by its antennas. The transmit weights and receive weights are determined to optimize the link margin, e.g., optimize the signal-to-noise ratio of signals received by one device from the other. Techniques related to joint maximal ratio combining, also called composite beamforming (CBF), are the subject matter of above-identified commonly assigned co-pending application. These techniques significantly extend the range of communication between the two communication devices.

An approach is desired for a joint maximal ratio combining technique that requires relatively low complexity computations be performed in a communication device.

SUMMARY OF THE INVENTION

A spatial signal processing system and method are provided to optimize the received signal-to-noise ratio (SNR) at a radio communication device based on the transmit filter at another radio communication device. An iterative process is provided to determine complex weights for tapped delay-line transmit filters at each of two communication devices that optimize the received SNR. When one communication device receives a signal from another device, it generates a receive filter matrix from a signal received by its one or more antennas. The receive filter matrix is comprised of one or more sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter for the one or more antennas. The receiving device computes the eigenvector corresponding to the maximum eigenvalue of a product of the receive filter matrix and a Hermitian of the receive filter matrix. This eigenvector is the principal eigenvector of that matrix multiplication product. The principal eigenvector is comprised of one or more sub-vectors each having a length corresponding to a number of taps of a transmit tapped-delay line filter associated with the one or more antennas. From the one or more sub-vectors of the principal eigenvector one or more transmit filter sub-vectors that form a transmit filter vector are determined. Each transmit filter sub-vector corresponds to the one or more antennas of the second communication device and defining one or more complex weights associated with the transmit tapped-delay line filter for the one or more antennas of the second communication device. The transmit filter vector is used by that device transmitted a signal back to the other device. The two communication devices will ultimately converge to transmit filter vectors that optimize the received SNR at the output of the receive filters of the other device. The range of communication, i.e., distance between the devices, is significantly increased using the techniques described herein.

The above and other objects and advantages will become more readily apparent when reference is made to the following description taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of two communication devices performing time- domain based composite beamforming.

FIG. 2 is a diagram showing an exemplary channel matrix. FIG. 3 is a diagram showing exemplary transmit filter vectors. FIG. 4 is a flow diagram illustrating an iterative process for time-domain based composite beamforming between two communication devices.

FIG. 5 is a graphical diagram showing exemplary results of the time- domain based iterative process.

FIG. 6 is a graphical diagram showing performance loss for ideal channel conditions.

FIG. 7 is a graphical diagram showing performance loss for the iterative process.

FIG. 8 is a block diagram of a communication device suitable for implementing the time-domain composite beamforming signal processing.

DETAILED DESCRIPTION OF THE DRAWINGS Referring first to FIG. 1, two radio communication devices 100 and 200 are shown that communicate with each other across a wireless transmission chamiel that can be defined by a channel matrix H (or H^τ, where ^τ denotes the transpose operator). When the signal-to-noise ratio (SNR) at the output of the receive filters of one device is optimized with respect to the transmit filters at the other device, the ideal transmit filter vector w_τ is given by the eigenvector corresponding to the maximum eigenvalue e_maxof (H^HH), which is the principal eigenvector of (H^HH), where ^H denotes the Hermitian operator. This ideal case assumes that the devices have direct knowledge of the channel, obtain from training sequences or from a separate signal containing channel information that is transmitted from one device to the other. Described below is a system and method to optimize the SNR at the output of the receive filters of one device (hereinafter referred to as the received SNR) with respect to tapped delay-line transmit filters at another device without direct knowledge of the channel between the devices. Using an estimate of the channel obtained from a signal received at one device from another device, an iterative process is provided that determines the transmit filters at the communication device at each iteration. The transmit filters at each device converge to a received SNR that is within l-2dB of the ideal case SNR in about 2 to 3 iterations for more than 90% of channel realizations.

With this background, communication device 100 includes, among other components, a transmit shaping filter 110, a plurality of transmit antenna filters 120 and N plurality of antennas 130. There is a transmit antenna filter 120 associated with each antenna 130. The transmit antenna filter 120 is, for example, a tapped delay-line filter having a number of taps. For each tap of the tapped delay-line filter, there is a complex weight having a magnitude component and a phase component. For example, a single tap delay-line filter has a single weight, and therefore a flat or constant magnitude and a flat or constant phase response across frequency. The characteristic of each transmit filter 120 is defined by a transmit filter sub-vector Y_T._DI,, where i is the antenna index (i = 1 to N), and the length of the transmit filter sub-vector corresponds to the number of taps of the transmit antemia filter 120. The entry in each sub-vector defines the corresponding tap weight for the delay-line filter. The transmit filter sub-vectors can be grouped together form a transmit filter vector. The filter vector and sub-vectors will be described further hereinafter.

Similarly, for purposes of processing a received signal, the communication device 100 comprises a plurality of receive antenna filters 140 and a combiner/detector 150. There is a receive antenna filter 140 coupled to an associated antenna 130. Each receive antenna filter 140 is, for example, a tapped delay-line filter having a number of taps, and is essentially a matched filter. A combiner/equalizer 150 is coupled to the receive antenna filters 140. The characteristic of each receive filter 140 is defined by a receive filter sub-vector

Y_R,_D2 having a length corresponding to the number of taps of the receive antenna filters 140. The entry in each receive

defines the corresponding complex tap weight for the delay-line filter. There are computation elements or blocks represented by reference numeral 160 in communication device

100 that perform discrete signal computations with respect to the transmit antenna filters 120 and receive antemia filters 140 described hereinafter. Communication device 200 includes components similar to those in communication device 100. Communication device includes a plurality of antennas 210, a plurality of receive antenna filters 220 and a combiner/equalizer 230. There is a receive antenna filter 220 (i.e., a matched filter) associated with each antenna 210. The communication device 200 has M plurality of antennas. The characteristic of each receive anteima filter 220 is defined by a receive filter sub-vector _R__D2, where j is the antenna index (j = 1 to M). The receive filter sub- vectors can be grouped together form a receive filter vector. On the transmit side, there is a transmit shaping filter 240 and a plurality of transmit antenna filters 250 each associated with a corresponding one of the antennas 210. The characteristic of each transmit antenna filter 250 is defined by a transmit filter sub-vector Yτ_,D2- Like communication device 100, the receive antenna filters 220 and the transmit antenna filters 250 are, for example, tapped delay-line filters of a number of taps. The length of the receive filter sub-vectors _RιD correspond to the number of taps of the receive antemia filters 220, and the length of the transmit filter sub-vectors γ τ_,D2 correspond to the number of taps of the transmit antenna filters 250.

Communication device 200 has computation elements or blocks represented by reference numeral 260 that perform discrete signal computations with respect to the transmit antenna filters 210 and receive antenna filters 250 described hereinafter. While FIG. 1 shows that communication devices 100 and 200 each have a plurality of antemias, it should be understood that one of them, for example, communication device 200, may have a single antenna (and therefore a single transmit anteima filter and a single receive antenna filter). In this case, only one of the two devices of the communication link adapts its transmit filter to optimize the receive SNR at the device with the single anteima. The device with multiple antennas will adapt its receive filter to optimize its receive SNR from the device with a single antenna.

The communication device block diagram shown in FIG. 1 is useful in a transceiver that processes signals of any wireless communication modulation standard or format. Likewise, the methods described herein are applicable to any wireless communication modulation standard or format. An example is a code division multiple access (CDMA) format using a single carrier. A more specific example is the single-carrier scheme of the IEEE 802.11b short-range wireless standard.

It should be understood to those of skill in the art that FIG. 1 is a simplification of a communication device architecture to highlight those components relevant to the composite beamforming techniques described herein. For example, FIG. 1 omits (for the sake of conciseness) digital-to-analog converters and a radio frequency (RF) section between the antennas and the antenna filters. FIG. 8, described hereinafter, is an example of a more complete exemplary block diagram of a communication device. The components shown in FIG. 1 are elements that typically are included in a baseband section of a communication device and may be implemented by discrete elements or by field programmable gate arrays for digital signal processing integrated circuit implementations. The combiner/equalizer 150 (and 230) is meant to represent any suitable signal processing components used in a receiver. For example, in the case of a decision feedback equalizer (DFE), the combiner/equalizer block includes feedforward filters, a decision block and a feedback filter. In the case of a maximum likelihood sequence estimator (MLSE) receiver, there is a MLSE in the combiner/equalizer block 160 (and 230), and in the case of a direct sequence spread spectrum (DSSS) receiver, there is a correlator in the combiner/equalizer block 160 (and 220).

When communication device 100 transmits a signal to communication device 200, the communication channel between the N plurality of antennas 130 and the M plurality of antennas 210 is defined by a channel matrix H of appropriate dimension as is shown in FIG. 2, described hereinafter. Similarly, when communication device 200 transmits a signal to communication device 100, the communication channel between the M plurality of antennas 210 and the N plurality of antennas 130 is defined by a chamiel matrix H .

Turning to FIG. 2, the channel matrix H is described in further detail. The chamiel response from an antenna i of communication device 100 to an antenna j of communication device 200 is defined by a channel response vector h^1J and can be modeled as a tapped delay-line filter having a length or number of taps L. The channel response vector h^1J can be written as shown in FIG. 2. The channel response vector can also be written as a convolution matrix H;J, where i is the index for the N plurality of antemias of communication device 100 and j is the index for the M plurality of antennas of communication device 200. The dimensions of the channel response matrix Hy is (L + LTD1 - 1) x LTD1, where LTD1 is the length of the transmit filters of the first communication device 100.

Referring back to FIG. 1, the transmit antenna filters 120 in communication device 100 have a length (i.e., number of taps), and the transmit antenna filters 250 in communication device 200 have a length. The lengths of the transmit antenna filters 120 and 250 are not necessarily the same, and are chosen according to implementation/performance requirements. Obviously, the more taps a filter has, the greater performance it will have, at the expense of implementation cost and complexity. The length of the receive antenna filters 140 in communication device 100 depends on the length of the transmit antenna filters 250 and the length of the channel response vector h^1J suitable for modeling the channel response between the first and second communication devices. It can be shown that the length of the receive antenna filters 140 (when receiving a signal from communication device 200) is equal to the sum of the length of the transmit antenna filters 250 plus the length of the channel response vector h^1J. Similarly, the length of the receive antenna filters 210 (when receiving a signal from communication device 100) is equal to the sum of the length of the transmit antemia filters 120 plus the length of the channel response vector h^1J. The length of the transmit antenna filters 120 and 250 do not depend on the length of the receive antenna filters 140 and 210, respectively, and can be set to any desired length. For example, it has been determined through simulation that transmit antenna filters 120 and 250 can be single tap delay-line filters and still achieve acceptable performance.

With reference to FIG. 3, similar to the channel matrix H, there is a transmit filter matrix W'_T,DI associated with each antenna i of the first communication device 100 (for transmitting a signal to the second communication device 200). A transit filter super matrix is matrix comprising a plurality of sub-matrices corresponding to the transmit filter matrix associated with each antenna i. The transmit filter matrix W¹ _T,_DI is a convolution matrix representation of the corresponding transmit antenna filter sub-vector W_T._DI- The transmit antenna filter vector W_T,DI is essentially a super- vector comprised of a plurality of transmit filter sub-vectors Y_T,DJ, each transmit filter sub-vector corresponding to or associated with a transmit filter (FIG. 1), which in turn is associated with one of the plurality of antennas of the first communication device 100. For notation purposes, the length of each transmit filter sub-vector of communication device 100 is LTD1, as described above in conjunction with FIG. 2. Therefore, the length of the transmit antenna filter vector is N * LTD 1. The dimensions of each transmit filter matrix is (LTD1 + L - l) x L, and the dimension of each transmit filter sub- vector is LTD1 l.

Though not shown in FIG. 3, the transmit filter vector of the second communication device 200 (for transmitting a signal to the first communication device 100) is similarly defined as γyτ_,D2, associated with each antenna j of the second communication device 200. The length of the transmit antenna filter sub- vector (and thus the number of taps of the transmit antenna filters 250) for the second communication device 200 is denoted LTD2. The receive filter matrix for the first communication device is denoted ^_D./, and the receive filter matrix for the second communication device is denoted W_R,D2- Each receive filter matrix comprises a sub-matrix for each antenna of that device. Each sub-matrix is a convolution matrix derived from the receive filter sub-vector associated with the corresponding antenna depicted in FIG. 3. The filter length LTD1 of the first communication device and the filter length of LTD2 of the second communication device need not be the same. FIG. 4 illustrates the iterative process 400. The process 400 is described with respect to communication between the first communication device (denoted by the index Dl) having N antennas and the second communication device

(denoted by the index D2) having M antennas. It is to be understood that the process is applicable to any wireless communication application, such as, for example, a short-range wireless application. The process begins in step 410 when the first communication device transmits a signal to the second communication device using an initial transmit filter vector W^_DI, _O = [ 10...0, 10...0, 10...0, 10...0] according to the notation shown, normalized by the factor 1/(N) , where N is the nmnber of antennas of the first communication device. The purpose of this factor will be described hereinafter. The initial transmit filter vector has a unity value at the initial position in each sub-vector for each antenna. In step 410, the first communication device transmits a signal with the initial transmit filter vector to the second communication device. The second communication device receives the transmitted signal, and from the received signal, the second communication device estimates a vector corresponding to the product W^z^øeo, where e₀ is the vector [10...0]^τ. From this quantity, the second communication device obtains the initial receive filter vector W_R,_D2,_O and builds the receive filter matrix W^^o with dimensions that, after further computations, will result in a transmit filter vector wτ__D2 that has the desired filter length.

In step 420, the second communication device computes a principal eigenvector U_T__D which is the eigenvector corresponding to the maximum eigenvalue of the product of

■ The principal eigenvector uτ,D2,o has a length of M * LTD2. The principal eigenvector uτ,D2,o s a super vector, or vector of sub- vectors, where each sub-vector uJτ,_D2,o has a length LTD2 and is used to derive the transmit antenna filter sub-vector Yτ,_D2,o for a corresponding antenna of the second communication device.

Each transmit filter sub-vector Yτ_,D2 can take on one of two values as shown in FIG. 4. In one case, the transmit filter sub-vector γy τ,D2 is equal to the corresponding sub-vector u[τ,D2,o of the principal eigenvector uτ,D20- This is called the non-equal gain case indicated "NON-EG" in FIG. 4. hi another case, the transmit antenna sub-vector W_T,_D2 is equal to the corresponding sub-vector ιJτ_,D2,o of the principal eigenvector Uτ,w,o divided by the norm of that sub-vector [τ,m,o and by (M)'^λ. This case is called the equal-gain case, indicated "EG" in FIG. 4. This further computation equal-gain normalizes the magnitude of each filter sub- vector so that the power of the signal transmitted at each antenna using the transmit filter sub-vectors is equal. This equal gain constraint is advantageous because it has been found to yield performance very close to non-equal gain anteima processing (within 1-2 dB), but substantially reduces the power output requirements for each power amplifier associated with each antenna. The advantages of equal-gain composite beamforming are further described in the aforementioned co-pending application entitled "System and Method for Antenna Diversity Using Equal Gain Joint Maximal Ratio Combining." The initial transmit filter sub-vectors used by the first communication device in step 410 can optionally be equal gain normalized, as indicated in FIG. 4 with the (N)'^λ factor.

In step 420, the first communication device receives the signal transmitted by the second communication device using the transmit sub-vectors Wτ,_D2 and estimates a vector corresponding to the product W^_DI to obtain the initial receive filter vector W >_DI,_O- At the next iteration in step 430, the first communication device performs a process similar to the one performed by the second comm iication device in step 420, to compute the principal eigenvector U_T,DI,I and generate therefrom updated transmit filter sub- ectors for each antemia of the first communication device using either the equal gain computation or non- equal gain relationship. It should be noted that in the even LTD1 is not equal to LTD2.

Steps 440 and 450 show that this process repeats and the transmit filter sub- vectors at the first and second communication devices converge to values that optimize the received SNR at each of them. The transmit filter sub-vectors computed at each iteration are stored. Even though the transmit filter sub-vectors will ultimately converge after several iterations, they can be continuously updated with each transmission between those communication devices beyond convergence. In addition, it may also be desirable to store the most recent or updated transmit filter sub-vectors in one communication device against and identifier of the particular destination communication device. In this way, when a subsequent communication session is initiated between those same communication devices, each device can retrieve the stored transmit filter sub-vectors for use in transmitting signals to the other device.

Optimizing the transmit filters at the first and second communication device in this way significantly increases the range (i.e., distance) between the devices.

This can be very advantageous in a wireless communication environments, such as short-range wireless applications. A wireless LAN is one example of a short-range wireless application.

The computations referred to in the description of the iterative process 400 may be performed by the discrete signal computation blocks 160 and 260 (using digital signal processing techniques), respectively, in communication devices 100 and 200. For example, when communication device 100 or 200 receives a signal from the other device, there is a channel estimator computation block that estimates the composite channel transmit filter response of the transmitting communication device in order to determine the receive super matrix W_R. There is a computation block that forms the receive vector W_R and from that vector builds the receive convolution matrix W^J _R for each antenna. There are also one or more computation blocks that compute super matrix W_R, the Hermitian of the receive super matrix W_R, multiply it with the receive matrix WR and compute the principle or principal eigenvector of the matrix product of that matrix multiplication. Computation blocks are also provided that normalize each sub-vector (divide by the norm of the principal eigenvectors and by the square-root of the number of antennas) for each antenna sub-vector. Moreover, the transmit antenna filters and receive antemia filters in each communication device may similarly be implemented by computational blocks.

It may be desirable for a first device initiating communication with a second device to transmit an initial signal or packet to the second device using transmit delay diversity (TDD) techniques to increase the likelihood that the second device will receive the initial packet, and therefore be able to beamform back a packet to the first device. TDD techniques essentially increase the range of the initial packet and are particularly useful when the channel with the other device is not known, hence transmit beamforming a signal to that device would not ensure reception by the other device. This is the case when transmitting a packet for the first time.

This may be useful when one communication device has not been in communication with another particular communication device for a significant period of time. The channel may be different due to a new location of one or both of the devices and when new objects or obstructions have been placed in the channel between the devices. Also, an existing communication link may be lost, and efforts to re-establish it with composite beamforming may not work.

In any event, the initial packet is transmitted, in step 410 of FIG. 4, using

TDD techniques rather than with an arbitrary transmit weight vector. For example, the AP may transmit the initial packet to a STA using TDD. The initial packet may be a broadcast packet, such as a beacon in LEEE 802.11 parlance, or a directed packet. When transmitting an initial packet using TDD, the signal to be transmitted is multiplied by a transmit weight vector (e.g., filtered by a transmit filter vector) that performs the TDD function, i.e., x(t + τ). hi the general case where the transmit filter length (LTD) is longer than the number of transmit antennas times, the number of symbols delayed per antenna (i.e. LTD ≥ N*SD, where SD is the number of symbols delayed per antenna), then the initial transmit weights would be wτ,Di,i,o ⁼ l/sqrt(N) * ej, where e\ is a unit vector with all elements equal to 0 except the ith element which is 1, where i is the antenna index, for i = 1 to N. For example ei = [1,0,0,....]; §₂ ~ [0,1,0,0,...], e = [0,0,1,0,0,...], etc. However, in the case where LTD < N*SD (which is the case when a single tap filter is used for each antenna, i.e. LTD = 1, and the device has at least two antennas), there are not enough taps in the filter to delay the signal using the filter, so a separate input buffer may be used in advance of each filter (e.g., placing a buffer before each transmit filter 120 in FIG. 1) to generate a delay. For example, for a two antenna case, there are two buffers, the first buffer would have the read and write pointers starting from the same location (implying no delay) whereas the second buffer would have the read pointer lagging the write pointer by SD symbols (implying SD symbol delay). The STA would receive the initial packet sent using TDD, receive match to the received initial packet and then generate transmit weights (as described above in conjunction with FIG. 4) from the receive weights used to combine the received signals, for transmitting a packet to the AP as shown in step 420. From then on, the process continues as shown in FIG. 4. That is, the AP receives the packet from the

STA, and will receive match to it (gaining knowledge about the chamiel) to compute transmit weights for transmitting to that STA. The same technique may be used in the reverse direction, whereby the STA transmits an initial packet to the AP using TDD. For example, in the IEEE 802.11

WLAN example, a STA may turn on and either listen for a beacon from an AP or transmit a probe request to the AP. If the STA receives a beacon signal, it can receive match to it, generate a transmit weight vector, and transmit a packet back to the AP using transmit beamforming, and the process of FIG. 4 will proceed as described above. On the other hand, if the STA does not wait for a beacon, and instead transmits a probe request signal to the AP, it will transmit the probe request signal using TDD to increase the range of the probe request to increase the chance that the AP will receive it. Then, the AP can receive match, and beamform back to the STA, and the process of FIG. 4 will proceed as described above.

FIGs. 5 to 7 show various performance metrics of the iterative scheme. FIG. 5 shows the loss in SNR of the iterative scheme of FIG. 4 relative to the case where the channel state is known at the transmitting device (hereinafter called the "ideal case"). The loss in SNR due to the iterative scheme is less than 2 dB for more than 90% of channel realizations.

FIG. 6 shows loss in SNR using the equal gain constraint relative in the ideal case relative to the non-equal gain ideal case. That is, both communication devices, when transmitting to the other device, constrain the power of the signal at each antenna to be equal. The loss in SNR for the equal gain case is less than 1 dB for more than 90% of channel realizations.

FIG. 7 shows the loss in SNR using the equal gain constraint in the iterative scheme of FIG. 4. The loss in SNR using equal gain is less than 1 dB for more than 90% of channel realizations.

FIG. 8 shows a more complete exemplary block diagram of a communication device useful in accordance with the techniques described herein. The communication devices at both ends of the lin , i.e., devices 100 and 200 may have any known suitable architecture to transmit, receive and process signals. An example of a coirrmunication device block diagram is shown in FIG. 8. The communication device comprises an RF section 310, a baseband section 320 and optionally a host 330. There are a plurality of antemias, e.g., four antennas 302,

304, 306, 308 coupled to the RF section 310 that are used for transmission and reception. The RF section 310 has a transmitter (Tx) 312 that upconverts baseband signals for transmission, and a receiver (Rx) 314 that downconverts received RF signals for baseband processing, h the context of the composite beamforming techniques described herein, the Tx 312 upconverts and supplies separately weighted signals to corresponding ones of each of the plurality of antennas via separate power amplifiers. Similarly, the Rx 314 downconverts and supplies received signals from each of the plurality of antennas to the baseband section 320. The baseband section 320 performs processing of baseband signals to recover the information from a received signal, and to convert information in preparation for transmission. The baseband section 320 may implement any of a variety of communication formats or standards, such as WLAN standards IEEE 802.1 lx, frequency hopping standards such as Bluetooth™, as well as other protocol standards, not necessarily used in a WLAN. In the case of frequency hopping systems, the anteima sub-vectors are computed and stored for each frequency in a frequency hopping sequence. The intelligence to execute the computations for the composite beamforming techniques described herein may be implemented in a variety of ways. For example, a processor 322 in the baseband section 320 may execute instructions encoded on a processor readable memory 324 (RAM, ROM, EEPROM, etc.) that cause the processor 322 to perform the composite beamforming steps described herein. Alternatively, as suggested above, an application specific integrated circuit (ASIC) may be fabricated with the appropriate firmware e.g., field programmable gate arrays (FPGAs), configured to execute the computations described herein. This ASIC may be part of, or the entirety of, the baseband section 320. For example, the components shown in FIG. 1 as part of the communication devices may be implemented by FPGAs in the baseband section 320. Still another alternative is for the beamforming computations to be performed by a host processor 332 (in the host 330) by executing instructions stored in (or encoded on) a processor readable memory 334.

The RF section 310 may be embodied by one integrated circuit, and the baseband section 320 may be embodied by another integrated circuit. The communication device on each end of the communication link need not have the same device architecture or implementation.

To summarize, a method is provided for communicating signals between a first communication device and a second communication device using radio frequency (RF) communication techniques. At the first communication device there are steps of generating a transmit filter vector for processing a signal to be transmitted from the first communication device to the second communication device, the transmit filter vector comprised of a plurality of transmit filter sub- vectors defining one or more complex weights associated with a transmit tapped- delay line filter, each transmit filter sub-vector associated with a corresponding one of a plurality of antennas of the first communication device and having a length corresponding to the number taps of the associated transmit tapped-delay line filter; and applying the transmit filter vector to a signal to be transmitted from the first communication device to the second communication device. At the second communication device there are steps of generating a receive filter matrix from a signal received by the one or more antennas of the second communication device from the first communication device, the receive filter matrix comprised of one or more sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter for the one or more antennas of the second communication device; computing a principal eigenvector of a product of the receive filter matrix and a

Hermitian of the receive filter matrix, the principal eigenvector comprised of one or more sub-vectors each having a length corresponding to a number of taps of a transmit tapped-delay line filter associated with the one or more antennas of the second communication device; deriving from the one or more sub-vectors of the principal eigenvector one or more transmit filter sub-vectors that form a transmit filter vector, each transmit filter sub-vector corresponding to the one or more antennas of the second communication device and defining one or more complex weights associated with the transmit tapped-delay line filter for the one or more antennas of the second communication device; and applying the transmit filter vector at the second communication device to a signal to be transmitted from the second communication device to the first commmiication device. The transmit filter vector at either or both of the first and second communication devices may be normalized at each sub-vector so that the total power associated with a transmitted signal is divided equally among the plurality of antennas of the first communication device.

Similarly, a method is provided for radio commmiication between a first communication device and a second communication device, comprising steps of generating a transmit filter vector for processing a signal to be transmitted from the first communication device to the second communication device, the transmit filter vector comprised of a plurality of transmit filter sub-vectors defining one or more complex weights associated with a transmit tapped-delay line filter, each transmit filter sub-vector associated with a corresponding one of a plurality of antemias of the first communication device and having a length corresponding to the number taps of the associated fransmit tapped-delay line filter; applying the transmit filter vector to a signal to be transmitted from the first coirimumcation device to the second communication device; generating a receive filter matrix from a signal received by the plurality of antennas of the first communication device from the second communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub- vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter process for the each of the plurality of antennas of the first communication device; computing a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub-vectors each having a length corresponding to the number of taps of the transmit tapped-delay line filter process of the first communication device; and updating from the plurality of sub-vectors of the principal eigenvector the plurality of transmit filter sub-vectors. This method may be implemented by instructions encoded on a medium, such as a processor readable medium, or by instructions that program a field programmable gate array, or that define a plurality of digital logic gates in silicon in an integrated circuit.

Further still, a semiconductor device is provided comprising a plurality of field programmable configured, or fixed digital logic gates defined, to implement: a plurality of transmit tapped delay-line filters, each associated with a corresponding one of a plurality of antennas; a plurality of receive tapped delay-line filters, each associated with a corresponding one of the plurality of antennas; and one or more computation blocks that generate a transmit filter vector for processing a signal to be transmitted to another communication device, the transmit filter vector comprised of a plurality of transmit filter sub-vectors defining one or more complex weights associated with the transmit tapped-delay line filter, each transmit filter sub- vector associated with a corresponding one of the plurality of antennas and having a length corresponding to the number taps of the associated transmit tapped-delay line filter; apply the transmit filter vector to a signal to be transmitted from the other communication device; generate a receive filter matrix from a signal received by the plurality of antennas from the other communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter process for the each of the plurality of antennas; compute a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub- vectors each having a length corresponding to the number of taps of the transmit tapped-delay line filter process; and update from the plurality of sub-vectors of the principal eigenvector the plurality of transmit filter sub-vectors. The semiconductor device may be, for example, an digital application specific integrated circuit implemented using field programmable gate arrays or digital logic implementations, such as CMOS digital logic.

The above description is intended by way of example only.

Claims

What is claimed is:

1. A method for communicating signals between a first communication device and a second communication device using radio frequency (RF) communication techniques, comprising: a. at the first communication device: i. generating a transmit filter vector for processing a signal to be transmitted from the first communication device to the second communication device, the transmit filter vector comprised of a plurality of transmit filter sub- vectors defining one or more complex weights associated with a transmit tapped-delay line filter, each transmit filter sub-vector associated with a corresponding one of a plurality of antennas of the first communication device and having a length corresponding to the number taps of the associated transmit tapped-delay line filter; and ii. applying the transmit filter vector to a signal to be transmitted from the first communication device to the second communication device; b. at the second communication device: i. generating a receive filter matrix from a signal received by the one or more antennas of the second communication device from the first coimnunication device, the receive filter matrix comprised of one or more sub-matrices each being a convolution matrix derived from a receive filter sub- ector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter for the one or more antennas of the second communication device; ii. computing a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of one or more sub- vectors each having a length corresponding to a number of taps of a fransmit tapped-delay line filter associated with the one or more antennas of the second communication device; iii. deriving from the one or more sub-vectors of the principal eigenvector one or more transmit filter sub-vectors that form a transmit filter vector, each transmit filter sub-vector corresponding to the one or more antemias of the second communication device and defining one or more complex weights associated with the transmit tapped-delay line filter for the one or more antennas of the second communication device; and iv. applying the transmit filter vector at the second communication device to a signal to be transmitted from the second communication device to the first communication device.

2. The method of claim 1 , wherein the step of generating the transmit filter vector at the first communication device further comprises normalizing each sub-vector of the fransmit filter vector so that the total power associated with a transmitted signal is divided equally among the plurality of antemias of the first communication device.

3. The method of claim 1 , wherein the step of deriving the one or more transmit filter sub-vectors for the second communication device comprises equating each transmit filter sub-vector to the corresponding sub-vector of the principal eigenvector.

4. The method of claim 1 , wherein the step of deriving the one or more transmit filter sub-vectors at the second communication device further comprises computing the norm of each of a plurality of sub- vectors of the principal eigenvector and dividing each sub-vector of the principal eigenvector by the nonn and by the square root of the number of plurality of antennas of the second communication device so that the power of the signal transmitted by the second communication device is divided equally among the plurality of antennas of the first communication device.

5. The method of claim 1, and further comprising at the first communication device steps of: iii. generating a receive filter matrix from a signal received by the plurality of antennas of the first communication device from the second communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each sub-vector defines one or more complex weights associated with a receive tapped-delay line filter for a corresponding one of the plurality of antennas of the first communication device; iv. computing a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub-vectors each having a length corresponding to the number of taps of the transmit tapped- delay line filter of the first communication device; and v. updating from the plurality of sub-vectors of the principal eigenvector the plurality of fransmit filter sub-vectors.

6. The method of claim 5, and further comprising repeating steps (iii) through (v) at the first communication device and steps (i) through (iv) at the second communication device for signals transmitted between the first and second communication devices, to converge to transmit filter vectors at the first and second communication devices that optimize the signal-to-noise ratio of signals communicated between them.

7. The method of claim 5, wherein the step of updating the transmit filter sub- vectors of the first communication device comprises equating each fransmit filter sub-vector to the corresponding sub-vector of the principal eigenvector computed by the first communication device.

8. The method of claim 5, wherein the step of updating the transmit filter sub- vectors of the first communication device comprises computing the norm of each of a plurality of sub-vectors of the principal eigenvector and dividing each sub-vector of the principal eigenvector by the norm and by the square root of the number of plurality of antennas of the first communication device.

9. The method of claim 1 , wherein the step of generating the transmit filter vector for transmitting an initial signal from the first communication device to the second communication device comprises generating a transmit filter vector to perform transmit delay diversity on the initial signal when applied to the initial signal for transmission to the second communication device.

10. A method for radio communication between a first communication device and a second communication device, comprising: a. generating a transmit filter vector for processing a signal to be transmitted from the first communication device to the second communication device, the transmit filter vector comprised of a plurality of transmit filter sub-vectors defining one or more complex weights associated with a transmit tapped-delay line filter, each transmit filter sub-vector associated with a corresponding one of a plurality of antennas of the first communication device and having a length corresponding to the number taps of the associated transmit tapped- delay line filter; b. applying the transmit filter vector to a signal to be transmitted from the first communication device to the second communication device; c. generating a receive filter matrix from a signal received by the plurality of antennas of the first communication device from the second communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter process for the each of the plurality of antennas of the first commmiication device; d. computing a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub-vectors each having a length corresponding to the number of taps of the transmit tapped-delay line filter process of the first communication device; and e. updating from the plurality of sub-vectors of the principal eigenvector the plurality of transmit filter sub-vectors.

11. The method of claim 10, wherein the step of updating comprises equating each transmit filter sub-vector to the corresponding sub-vector of the principal eigenvector.

12. The method of claim 10, wherein the step of updating further comprises computing the norm of each of a plurality of sub-vectors of the principal eigenvector and dividing each sub-vector of the principal eigenvector by the norm and by the square root of the number of plurality of antennas of the first communication device so that the power of the signal transmitted by the first communication device is divided equally among the plurality of antennas of the first communication device.

13. The method of claim 10, and further comprising repeating steps (c) through (e) for each signal received at the first communication device from the second communication device to update the transmit filter vector at the first communication device for transmission of signals from the first communication device to the second communication device.

14. The method of claim 10, wherein the step of generating the transmit filter vector for transmitting an initial signal from the first communication device to the second communication device comprises generating a transmit filter vector to perform transmit delay diversity on the initial signal when applied to the initial signal for transmission to the second communication device.

15. A medium encoded with instructions that, when executed, perform a method comprising the steps of: a. generating a transmit filter vector for processing a signal to be transmitted from a first communication device to a second communication device, the transmit filter vector comprised of a plurality of transmit filter sub-vectors defining one or more complex weights associated with a transmit tapped-delay line filter, each fransmit filter sub-vector associated with a corresponding one of a plurality of antemias of the first communication device and having a length corresponding to the number taps of the associated transmit tapped- delay line filter; b. applying the transmit filter vector to a signal to be transmitted from the first communication device to the second communication device; c. generating a receive filter matrix from a signal received by the plurality of antennas of the first communication device from the second communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter process for the each of the plurality of antennas of the first communication device; d. computing a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub-vectors each having a lengft corresponding to the number of taps of the transmit tapped-delay line filter process of the first communication device; and e. updating from the plurality of sub-vectors of the principal eigenvector the plurality of transmit filter sub-vectors.

16. The medium of claim 15, wherein the instructions encoded on the medium for performing the step of updating comprises instructions for equating each transmit filter sub-vector to the corresponding sub-vector of the principal eigenvector.

17. The medium of claim 15, wherein the instructions encoded on the medium for performing the step of updating further comprise instructions that compute the nonn of each of a plurality of sub-vectors of the principal eigenvector and divide each sub-vector of the principal eigenvector by the norm and by the square root of the number of plurality of antennas of the first communication device so that the power of the signal transmitted by

¹ the first communication device is divided equally among the plurality of antennas of the first communication device.

18. The medium of claim 15, and further comprising instructions that repeat steps (c) through (d) for each signal received at the first communication device from the second communication device to update the transmit filter vector at the first communication device for transmission of signals from the first communication device to the second communication device.

19. The medium of claim 15, wherein the instructions encoded on the medium define digital logic gates that perform the computations of steps (a) through

(e).

20. The medium of claim 15, wherein the instructions are processor readable instructions, that when executed by a processor, cause the processor to perform steps (a) through (e).

21. A communication device comprising the medium of claim 15, and further comprising: a. transmitter to be coupled to the plurality of antennas to upconvert transmit signals for transmission via respective ones of the plurality of antennas; and b. a receiver to be coupled to the plurality of antennas to downconvert signals received by the plurality of antennas.

22. The medium of claim 15, wherein the instructions encoded on the medium for generating the fransmit filter vector for transmitting an initial signal from the first communication device to the second commmiication device comprises instructions for generating a fransmit filter vector to perform transmit delay diversity on the initial signal when applied to the initial signal for transmission to the second communication device.

23. A semiconductor device comprising a plurality of gates configured to implement: a. a plurality of transmit tapped delay-line filters, each associated with a corresponding one of a plurality of antennas; b. a plurality of receive tapped delay-line filters, each associated with a corresponding one of the plurality of antennas; c. one or more computation blocks that: i. generate a transmit filter vector for processing a signal to be transmitted to another communication device, the transmit filter vector comprised of a plurality of transmit filter sub-vectors defining one or more complex weights associated with the transmit tapped-delay line filter, each transmit filter sub-vector associated with a corresponding one of the plurality of antennas and having a length conesponding to the number taps of the associated transmit tapped-delay line filter; ii. apply the fransmit filter vector to a signal to be transmitted from the other communication device; iii. generate a receive filter matrix from a signal received by the plurality of antennas from the other communication device, the receive filter matrix comprised of a plurality of sub-matrices each being a convolution matrix derived from a receive filter sub-vector, wherein each receive filter sub-vector defines one or more complex weights associated with a receive tapped-delay line filter process for the each of the plurality of antennas; iv. compute a principal eigenvector of a product of the receive filter matrix and a Hermitian of the receive filter matrix, the principal eigenvector comprised of a plurality of sub-vectors each having a length corresponding to the number of taps of the transmit tapped-delay line filter process; and v. update from the plurality of sub-vectors of the principal eigenvector the plurality of transmit filter sub-vectors.

24. The semiconductor device of claim 23, wherein the computation blocks update the plurality of transmit sub-vectors by equating each transmit filter sub-vector to the corresponding sub-vector of the principal eigenvector.

25. The semiconductor device of claim 23, wherein the computation blocks update the plurality of transmit sub-vectors by computing the norm of each of a plurality of sub-vectors of the principal eigenvector and dividing each sub-vector of the principal eigenvector by the norm and by the square root of the number of the plurality of antennas so that the power of the signal transmitted is divided equally among the plurality of antennas.

26. A radio communication device comprising the semiconductor device of claim 23, and further comprising: a. a plurality of antennas ; b. transmitter to be coupled to the plurality of antennas to upconvert transmit signals for transmission via respective ones of the plurality of anteimas; and c. a receiver to be coupled to the plurality of antennas to downconvert signals received by the plurality of antennas.

27. The semiconductor device of claim 23, wherein the computation blocks that generate the transmit filter vector for processing an initial signal for transmission from the first communication device to the second communication device define a transmit filter vector that performs transmit delay diversity on the initial signal when processing the initial signal for transmission from the first communication device to the second communication device.