CN101478374B - Physical layer network code processing method - Google Patents

Abstract

The invention discloses an encoding operation method for physical-layer networks. The method comprises the following steps: a first source node broadcasts a first signal and a second source node broadcasts a second signal; a relay node receives a relay mixed signal, wherein the mixed signal is the signal that reaches the relay node after the first signal and the second signal are mixed and subjected to noise addition; a target node receives a first mixed signal, wherein the first mixed signal is the signal that reaches the target node after the first signal and the second signal are mixed and subjected to noise addition; the relay node broadcasts the relay mixed signal; the target node receives a second mixed signal, wherein the second mixed signal is the signal that reaches the target node after the relay mixed signal is subjected to noise addition; and the target node acquires estimated values of the first signal and the second signal according to the first mixed signal and the second mixed signal. The encoding operation method effectively utilizes the interference produced after the signal mixing, improves the network capacity, and increases the bandwidth utilization rate.

Description

Physical layer network code processing method

Technical field

The present invention relates to network coding technique, particularly relate to a kind of physical layer network code processing method, belong to communication technical field.

Background technology

Because the node in wireless network has mobility and portability, make the establishment of Wi-Fi conveniently, flexibly, wireless network has obtained general application.The link of wireless network has broadcast characteristic, and namely the node in wireless network can be to other a plurality of node broadcasts information, and same, the node in wireless network also can receive the information from other a plurality of nodes.Broadcast characteristic due to node, if a plurality of nodes in network are interior broadcast message at one time, can mutually mix in the free space of propagating between a plurality of signals that a plurality of node broadcasts are gone out, the mixing of signal can cause to produce between signal and disturb, and the information that causes receiving node to receive is inaccurate maybe can't receive required information.Therefore, be the generation that avoids interference, in prior art, the transmission method of information generally all adopts transmitted signal in succession to realize the transmission of information.

Fig. 1 is the structural representation of communication in the prior art wireless network; Fig. 2 is the sequential chart that in the prior art wireless network, in information transferring method, signal transmits.Have two source node S 1 and S2 in the assumed wireless network, via node R and destination node D, source node S 1 and S2 can be by via node R with communication to destination node D.As shown in Figure 2, in prior art, the communication process of source node S 1 and S2 and destination node D is as follows: at the first time slot T ₁₀, source node S 1 broadcast message, the information of via node R reception sources node S1 broadcasting; At the second time slot T ₂₀, via node R goes out the information broadcasting that the source node S 1 that observes is broadcasted, and is received the information of via node R broadcasting by destination node D, and destination node D obtains the information of source node S 1; At the 3rd time slot T ₃₀, source node S 2 broadcast messages, the information of via node R reception sources node S2 broadcasting; At the 4th time slot T ₄₀, via node R goes out the information broadcasting that the source node S 2 that observes is broadcasted, and is received the information of via node R broadcasting by destination node D, and destination node D obtains the information of source node S 2.Can find out, in prior art, two source nodes are during to same destination node transmission information, completing once that communication needs 4 time slots at least, communicate by letter if having between plural source node and destination node, and the time slot that needs will be more.

Can find out, in information transferring method, disturb for avoiding signal in the prior art wireless network, improve the accuracy of communication, when communicating by letter between a plurality of source nodes and same destination node, the time slot of completing primary information transmission needs is too much, make the network whole volume little, bandwidth availability ratio is low.

Summary of the invention

The purpose of this invention is to provide a kind of physical layer network code processing method, can effectively utilize signal to mix the rear interference that produces, improve bandwidth availability ratio, promote network capacity.

For achieving the above object, the invention provides a kind of physical layer network code processing method, comprising:

The first source node broadcasting first signal, the second source node broadcasting secondary signal;

Via node receives the relaying mixed signal, and described relaying mixed signal is that the signal that arrives described via node place after making an uproar is mixed, added to described first signal and secondary signal process; Destination node receives the first mixed signal, and described the first mixed signal is that the signal that arrives described destination node place after making an uproar is mixed, added to described first signal and secondary signal process;

The described relaying mixed signal of described via node broadcasting;

Described destination node receives the second mixed signal, and described the second mixed signal is described relaying mixed signal through adding the signal that arrives described destination node place after making an uproar;

Described destination node obtains the estimated value of first signal and secondary signal according to described the first mixed signal and the second mixed signal.

Wherein, described destination node comprises according to the estimated value of described the first mixed signal and the second mixed signal acquisition first signal and secondary signal:

With described the first mixed signal and the second mixed signal in conjunction with and obtain the observation signal Y of described destination node;

By Independent Component Analysis, described observation signal Y is processed, obtain the estimated value of described first signal and secondary signal.

Described described observation signal Y the processing by Independent Component Analysis comprises:

Described observation signal Y is carried out albefaction process, obtain whitened signal Z;

Described whitened signal Z is carried out analyzing and processing, obtain separation matrix V;

Obtain to comprise according to described separation matrix V and whitened signal Z the estimated matrix E:E=V that the estimated value by described first signal and secondary signal forms ^HZ。

Describedly described observation signal Y carried out albefaction process, obtain whitened signal Z and comprise:

Obtain covariance matrix R according to described observation signal Y _Y, and according to described covariance matrix R _YObtain the albefaction matrix W;

By described albefaction matrix W, described observation signal Y is carried out albefaction and process, obtain whitened signal Z:Z=WY.

Described according to described observation signal Y acquisition covariance matrix R _Y, and according to described covariance matrix R _YObtaining the albefaction matrix W comprises:

Obtain the covariance matrix R of described observation signal Y according to described observation signal Y _Y, described covariance matrix R _YFor:

$R_Y=E\left\{{\mathrm{YY}}^H\right\}=E\left\{(\mathrm{KX}+N){(\mathrm{KX}+N)}^H\right\}$

$=\mathrm{KE}\left\{{\mathrm{XX}}^H\right\}{K}^H+\mathrm{KE}\left\{{\mathrm{XN}}^H\right\}+E\left\{{\mathrm{NX}}^H\right\}{K}^H+E\left\{{\mathrm{NN}}^H\right\}$

$={\mathrm{KR}}_X{K}^H+{\mathrm{KR}}_{{\mathrm{XN}}^H}+R_{{\mathrm{NX}}^H}{K}^H+R_N$

$={\mathrm{KR}}_X{K}^H+R_N$

$={\mathrm{KR}}_X{K}^H+{\mathrm{\σ}}^2{I}_n$

Wherein, Y=KX+N, X are the source signal matrix that first signal and secondary signal consist of, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is noise matrix; Y ^HThe associate matrix of expression observation signal Y, R _XThe covariance matrix of expression source signal matrix X, R _NThe covariance matrix of expression noise matrix N,

With

Covariance matrix between expression source signal and noise, and With

Be 0; σ ²Be the variance of noise matrix N, I _nBe n * n rank unit matrix;

To determinant | λ I-XX ^H|=0 finds the solution, and obtains described covariance matrix R _YCharacteristic value { λ ₁, λ ₂..., λ _nAnd corresponding eigenvectors matrix A:A={a ₁, a ₂..., a _n, described characteristic value is that descending order is arranged;

Set matrix D: D=diag[(λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²)], wherein, diag () is that diagonal element is by (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) matrix that forms, { (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) be the characteristic value of observation signal Y;

Obtain described albefaction matrix W according to described matrix D and matrix A, described albefaction matrix W is: W=D ^-1/2A ^H=[(λ ₁+ σ ²) ^-1/2a ₁, (λ ₂+ σ ²) ^-1/2a ₂..., (λ _n+ σ ²) ^-1/2a _n] ^H

Described described whitened signal Z is carried out analyzing and processing, obtains separation matrix V and comprise:

According to described whitened signal Z, obtain the fourth order cumulant Q of described whitened signal Z _Z, and according to described fourth order cumulant Q _ZObtain described fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n}, according to described fourth order cumulant Q _ZFeature to obtaining characteristic set N _set: N _set={ λ _rM _r| 1≤r≤n}, wherein, λ _rBe characteristic value, M _rFor with λ _rThe matrix that corresponding characteristic vector forms, n is the number of observation signal;

By uniting diagonalization to described characteristic set N _setProcess, obtain described separation matrix V.

Described according to described fourth order cumulant Q _ZObtain described fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n} comprises:

With described fourth order cumulant Q _ZForm n ²* n ²Matrix Q;

Obtain characteristic value and the corresponding characteristic vector of described matrix Q according to described matrix Q, front n larger characteristic value and corresponding characteristic vector are formed described feature to { λ _r, M _r| 1≤r≤n}.

The described associating diagonalization that passes through is to described characteristic set N _setProcess, obtain described separation matrix V and comprise:

According to described characteristic set N _setTarget setting function C (V, N), described target function C (V, N) is:

$C(V,N)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{l=1}{\overset{n}{\mathrm{\Σ}}}\underset{k=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{Cum}(z_i,z_i^{*},z_l,z_k)\right|}^2=\underset{r=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{diag}\left(V^H{N}_{r}V\right)\right|}^2$

Wherein, set $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\′}& b_r^{\′}\\ c_r^{\′}& d_r^{\′}\end{array}\right],$ Diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V forms, a ' _r, b ' _r, c ' _r, d ' _rV ^HN _rThe coefficient of V, $N_r=\left[\begin{array}{cc}{a}_r& b_r\\ c_r& d_r\end{array}\right]$ Be characteristic set N _setIn an element, i, l, k ∈ [1, n] is the subscript of observation signal;

Described target function C (V, N) is carried out iteration optimization process, obtain described separation matrix V.

Describedly described target function C (V, N) carried out iteration optimization process, obtain described separation matrix V and comprise:

Set matrix T according to target function C (V, N), matrix T is:

$T=\underset{r}{\mathrm{\Σ}}{|a_r^{\′}-d_r^{\′}|}^2=P^T{G}^H\mathrm{GP}=P^T\mathrm{Re}\left(G^{H}G\right)P$

Wherein, a ' _r-d ' _r=(a _r-d _r) cos2 α+(b _r-c _r) sin2 α cos β+j (c _r-b _r) sin2 α sin β=P ^Tg _r, P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TMatrix Re (G ^HG) characteristic value characteristic of correspondence vector, g _r=[a _r-d _r, b _r+ c _r, j (c _r-b _r)] ^T, r=1 ..., n, G=[g ₁, g ₂..., g _n] ^T, Re () represents real;

Obtain Re (G ^HG) the eigenvalue of maximum characteristic of correspondence of matrix vector, and according to described eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TObtain corresponding α and β;

If Δ V ^H, Δ V has the structure of hermitian, and $\mathrm{\ΔV}=\left[\begin{array}{cc}\cos \mathrm{\α}& -e^{\mathrm{j\β}}\sin \mathrm{\β}\\ e^{-\mathrm{j\β}}\sin \mathrm{\α}& \cos \mathrm{\α}\end{array}\right],$ Carry out according to described α and β the updating value V that interative computation obtains separation matrix _new: V _new=V Δ V;

Updating value V according to described separation matrix _newUpgrade described eigenmatrix set N _setIn element N _r: N _r=Δ V ^HN _rΔ V;

Judge whether α satisfies the iteration stopping condition, if the updating value of the separation matrix of this moment is described separation matrix V.

Further, described according to also comprising before target function C (V, N) setting matrix T:

The described separation matrix V=I of initialization _n

Set described iteration stopping condition, described iteration stopping condition is | sin α | and＞1/100/ (n) ^1/2

In technical solution of the present invention, the mixed signal transmission is adopted in signal transmission between source node and destination node, the time slot that makes the signal transmission take reduces, therefore, saved the time of network node busy channel, improve the throughput of network node, effectively improved the integrated communication capacity of network, promoted network bandwidth utilization factor; Simultaneously, by adopting the ICA isolation technics that the mixed signal that destination node receives is processed, make the separating resulting of mixed signal accurately, reliably in technical solution of the present invention.

Description of drawings

Fig. 1 is the structural representation of communication in the prior art wireless network;

Fig. 2 is the sequential chart that in the prior art wireless network, in information transferring method, signal transmits;

Fig. 3 is the structural representation of signal transmission in physical layer network code processing method of the present invention;

Fig. 4 is the sequential chart of signal transmission in physical layer network code processing method of the present invention;

Fig. 5 is the schematic flow sheet of physical layer network code processing method of the present invention;

Fig. 6 is that in physical layer network code processing method of the present invention, destination node is carried out the schematic flow sheet of separating treatment to mixed signal;

Fig. 7 is the schematic flow sheet that the present invention processes observation signal.

Embodiment

Below by drawings and Examples, technical scheme of the present invention is described in further detail.

Fig. 3 is the structural representation of signal transmission in physical layer network code processing method of the present invention; Fig. 4 is the sequential chart of signal transmission in physical layer network code processing method of the present invention.Embodiment of the present invention technical scheme can be applicable in existing wireless network, different from method for transmitting signals in prior art is, in the embodiment of the present invention, signal is to transmit with hybrid mode, the signal that destination node receives is that a plurality of source node signals are through mixed signal, destination node can be carried out separating treatment to the mixed signal that receives, and obtains the signal that source node sends.Particularly, Fig. 5 is the schematic flow sheet of physical layer network code processing method of the present invention.The method comprises:

Step 1, the first source node broadcasting first signal, the second source node broadcasting secondary signal;

Step 2, via node receive the relaying mixed signal, and described relaying mixed signal is that the signal that arrives described via node place after making an uproar is mixed, added to described first signal and secondary signal process; Destination node receives the first mixed signal, and described the first mixed signal is that the signal that arrives described destination node place after making an uproar is mixed, added to described first signal and secondary signal process;

Step 3, the described relaying mixed signal of described via node broadcasting;

Step 4, described destination node receive the second mixed signal, and described the second mixed signal is described relaying mixed signal through adding the signal that arrives described destination node place after making an uproar;

Step 5, described destination node obtain the estimated value of first signal and secondary signal according to described the first mixed signal and the second mixed signal.

In the present embodiment, as shown in Figure 4, at the first time slot T ₁, the first source node S ₁With the second source node S ₂The signal that needs send is broadcasted away the first source node S ₁First signal and second source node S of broadcasting ₂The secondary signal of broadcasting is mixed in free space, is added and make an uproar, and first signal and secondary signal arrive respectively via node R and destination node D through the mixed signal of mixing, adding after making an uproar; Simultaneously, via node R and destination node D receive respectively relaying mixed signal and the first mixed signal; At the second time slot T ₂, via node R is transmitted to destination node D by the relaying mixed signal that will receive with the form of broadcasting; Simultaneously, destination node D receives process that via node forwards add the second mixed signal after making an uproar in free space transmission.So far, the first source node S ₁With the second source node S ₂And a signal between destination node D is transmitted, destination node D carries out separating treatment to the first mixed signal and the second mixed signal that receive, can obtain the estimated value of first signal and secondary signal, and with this first signal and secondary signal estimated value respectively as the first source node S ₁With the second source node S ₂Send to the information of destination node.In the present embodiment technical scheme, source node can be also more than three or three, and correspondingly, the signal that purpose receives is that a plurality of source node signals mix, add the mixed signal after making an uproar, destination node can be separated it equally, obtains the estimated value of the broadcast singal of each source node.

Particularly, in the present embodiment, destination node can adopt Blind Signal Separation (Blind SignalSeparation is called for short BSS) interface differential technique to receive the first mixed signal and the second mixed signal are carried out separating treatment.The BSS technology be one under the known condition of observation signal, isolate the technology of source signal, it can be in the situation that any channel condition of the unknown, realizes mixing, adding the observation signal of making an uproar and separate through wireless channel what receiving node was received, obtains the primary signal that sending node sends.Therefore, destination node (receiving node) obtains by the mixed signal that receives is carried out separating treatment the primary signal that source node sends.Can find out, can realize mixed signal is separated by the BSS technology, make a plurality of source nodes can transmit a signal to simultaneously destination node, be that signal can carry out the transmission of information with the form of mixed signal, make each source node and destination node carry out the timeslot number of signal transmission few, therefore, time and channel that the signal transmission takies reduce accordingly, improve the speed of signal transmission, effectively improved the whole message capacity of network, promoted the utilance of the network bandwidth.

Fig. 6 is that in physical layer network code processing method of the present invention, destination node is carried out the schematic flow sheet of separating treatment to mixed signal.On the basis of above-mentioned Fig. 5 technical scheme, step 5 can specifically comprise:

Step 51, with described the first mixed signal and the second mixed signal in conjunction with and obtain the observation signal Y of described destination node;

Step 52, by Independent Component Analysis, described observation signal Y is processed, obtain the estimated value of described first signal and secondary signal.

In above-mentioned steps 51, destination node can be processed the first mixed signal and the second mixed signal that receive, and as the observation signal Y of destination node, observation signal Y also can regard the mixed signal of all signals that each source node sends as.

In above-mentioned steps 52, destination node is carried out analyzing and processing by independent component analysis (Independent ComponentAnalysis is called for short ICA) method to observation signal Y, and obtains the signal that source node sends.

Particularly, suppose that the source signal matrix of the signal composition that each source node sends is X, the source signal matrix in the present embodiment $X=\left[\begin{array}{c}{x}_1\left[m\right]\\ x_2\left[m\right]\end{array}\right],$ X wherein ₁[m] is the first source node S ₁The first signal of broadcasting, x ₂[m] is the second source node S ₂The secondary signal of broadcasting, at this, also can be with x ₁[m], x ₂The first source node S that [m] obtains according to the ICA method as destination node ₁With the second source node S ₂Corresponding estimated value.Because wireless signal can be expressed as a discrete time function, therefore, the signal x[m that in the present embodiment, source node is broadcasted away] can be expressed as: x[m]=A _s[m] e ^{I θ s[m]}, A wherein _sBe the range value of signal, θ _sBe the phase place of signal, m is a number of samples that sends as the source node of signal source; The signal x[m that source node is broadcasted away] will be through decline, multipath and the phase shift of channel in spatial, so the signal that destination node (receiving node) receives can be expressed as x ' [m]: x ' [m]=k _ijA _s[m] e ^{I (θ s[m]+φ)}, k wherein _ij(i, j ∈ { s ₁, s ₂, r, d}) be signal from node j to the node i process amplitude attenuation factor on channel, and node j is to the distance dependent between node i, φ is the phase shift that signal produces on channel.

At the first time slot T ₁, the first source node S ₁With the second source node S ₂The signal x of broadcasting ₁[m], x ₂Signal when [m] arrives via node R can be expressed as respectively:

$x_1^{\′}\left[m\right]=k_{{\mathrm{rs}}_1}{A}_{s_1}\left[m\right]e^{i\left({\mathrm{\θs}}_1\right[m]+{\mathrm{\φ}}_1)}$

$x_2^{\′}\left[m\right]=k_{{\mathrm{rs}}_2}{A}_{s_2}\left[m\right]e^{i\left({\mathrm{\θs}}_2\right[m]+{\mathrm{\φ}}_2)}$

Because signal mixes in the space, adds and make an uproar, the relaying mixed signal that finally receives of via node is:

$y_r\left[m\right]=x_1^{\′}\left[m\right]+x_2^{\′}\left[m\right]+n_r\left[m\right]=k_{{\mathrm{rs}}_1}{A}_{s_1}\left[m\right]e^{i\left({\mathrm{\θs}}_1\right[m]+{\mathrm{\φ}}_1)}+k_{{\mathrm{rs}}_2}{A}_{s_2}\left[m\right]e^{i\left({\mathrm{\θs}}_2\right[m]+{\mathrm{\φ}}_2)}+n_r\left[m\right]$

Wherein, y _r[m] is the relaying mixed signal, n _r[m] is the noisy signal in source node arrival via node process.

Similarly, the first mixed signal of receiving of destination node is:

$y_{d_1}\left[m\right]=x_1^{\′\′}\left[m\right]+x_2^{\′\′}\left[m\right]+n_1\left[m\right]=k_{{\mathrm{ds}}_1}{A}_{s_1}\left[m\right]e^{i\left({\mathrm{\θs}}_1\right[m]+{\mathrm{\φ}}_1^{\′})}+k_{{\mathrm{ds}}_2}{A}_{s_2}\left[m\right]e^{i\left({\mathrm{\θs}}_2\right[m]+{\mathrm{\φ}}_2^{\′})}+n_1\left[m\right]$

Wherein,

Be the first mixed signal, $x_1^{\′\′}\left[m\right]=k_{{\mathrm{ds}}_1}{A}_{s_1}\left[m\right]e^{i\left({\mathrm{\θs}}_1\right[m]+{\mathrm{\φ}}_1^{\′})}$ It is the first source node S ₁The first signal x of broadcasting ₁Expression when [m] arrives destination node D, $x_2^{\′\′}\left[m\right]=k_{{\mathrm{ds}}_2}{A}_{s_2}\left[m\right]e^{i\left({\mathrm{\θs}}_2\right[m]+{\mathrm{\φ}}_2^{\′})}$ It is the second source node S ₂The secondary signal x of broadcasting ₂Expression when [m] arrives destination node D, n ₁[m] is the noise signal in source node signal arrival destination node process.

At the second time slot T ₂, the relaying mixed signal y of via node R broadcasting _r[m] arrives the signal at destination node D place for passing through the signal that adds after making an uproar, and the second mixed signal of receiving of destination node D is:

$y_{d_2}\left[m\right]=k_{\mathrm{dr}}\left(x_1^{\′}\right[m]+x_2^{\′}[m\left]\right)e^{i{\mathrm{\φ}}_r}+n_2^{\′}\left[m\right]+n_r\left[m\right]$

$=k_{\mathrm{dr}}{k}_{{\mathrm{rs}}_1}{A}_{s_1}\left[m\right]e^{i\left({\mathrm{\θs}}_1\right[m]+{\mathrm{\φ}}_1+{\mathrm{\φ}}_r)}+k_{\mathrm{dr}}{k}_{{\mathrm{rs}}_2}{A}_{s_2}\left[m\right]e^{i\left({\mathrm{\θs}}_2\right[m]+{\mathrm{\φ}}_2+{\mathrm{\φ}}_r)}+n_2\left[m\right]$

Wherein,

Be the second mixed signal, n ₂[m]=n _r[m]+n ' ₂[m] to be the source node signal arrive noisy signal in the destination node process, n ' by via node ₂[m] is the noisy signal in relaying mixed signal arrival destination node process.

Therefore, the observation signal Y that receives of destination node is: $Y=\left[\begin{array}{c}{y}_{d_1}\left[m\right]\\ y_{d_2}\left[m\right]\end{array}\right],$ And Y=KX+N is arranged, wherein, $K=\left[\begin{array}{cc}{k}_{{\mathrm{ds}}_1}{e}^{i{\mathrm{\φ}}_{{\mathrm{ds}}_1}}& k_{{\mathrm{ds}}_2}{e}^{i{\mathrm{\φ}}_{{\mathrm{ds}}_2}}\\ k_{\mathrm{dr}}{k}_{{\mathrm{rs}}_1}{e}^{i({\mathrm{\φ}}_{\mathrm{rs}1}+{\mathrm{\φ}}_{\mathrm{dr}})}& k_{\mathrm{dr}}{k}_{\mathrm{rs}}{e}^{i({\mathrm{\φ}}_{{\mathrm{rs}}_2}+{\mathrm{\φ}}_{\mathrm{dr}})}\end{array}\right]$ Be the hybrid matrix of signal amplitude and phase fading coefficient on channel, $N=\left[\begin{array}{c}{n}_1\left[m\right]\\ n_2\left[m\right]\end{array}\right]$ Add the matrix of making an uproar for signal on channel.

Can find out, only require that solving hybrid matrix K just can utilize above-mentioned Formula For Solving to go out X, can obtain the first source node S ₁The first signal value x of broadcasting ₁[m] and the second source node S ₂The secondary signal value x of broadcasting ₂[m].

Particularly, Fig. 7 is the schematic flow sheet that the present invention processes observation signal.On the basis of above-mentioned Fig. 6 technical scheme, in order to solve hybrid matrix K, the present embodiment carries out albefaction and separating treatment with observation signal Y, utilizes albefaction matrix W and separation matrix V to come estimated mixing matrix K, thereby obtains the first source node S ₁With the second source node S ₂The source signal matrix X that sends.Step 52 can specifically comprise:

Step 520, described observation signal Y is carried out albefaction process, obtain whitened signal Z;

Step 521, described whitened signal Z is carried out analyzing and processing, obtain separation matrix V;

Step 522, obtain to comprise according to described separation matrix V and whitened signal Z the estimated matrix E:E=V that the estimated value by described first signal and secondary signal forms ^HZ。

In above-mentioned steps 520, observation signal Y is carried out albefaction process, obtain whitened signal Z and comprise: obtain covariance matrix R according to described observation signal Y _Y, and according to described covariance matrix R _YObtain the albefaction matrix W; By described albefaction matrix W, described observation signal Y is carried out albefaction and process, obtain whitened signal Z:Z=WY.Wherein, obtain covariance matrix R according to observation signal Y _Y, and according to covariance matrix R _YObtaining the albefaction matrix W can specifically comprise:

Steps A 1, obtain the covariance matrix R of described observation signal Y according to described observation signal Y _Y, described covariance matrix R _YFor:

$R_Y=E\left\{{\mathrm{YY}}^H\right\}=E\left\{(\mathrm{KX}+N){(\mathrm{KX}+N)}^H\right\}$

$=\mathrm{KE}\left\{{\mathrm{XX}}^H\right\}{K}^H+\mathrm{KE}\left\{{\mathrm{XN}}^H\right\}+E\left\{{\mathrm{NX}}^H\right\}{K}^H+E\left\{{\mathrm{NN}}^H\right\}$

$={\mathrm{KR}}_X{K}^H+{\mathrm{KR}}_{{\mathrm{XN}}^H}+R_{{\mathrm{NX}}^H}{K}^H+R_N$

$={\mathrm{KR}}_X{K}^H+R_N$

$={\mathrm{KR}}_X{K}^H+{\mathrm{\σ}}^2{I}_n$

Wherein, Y=KX+N, X are the source signal matrix that first signal and secondary signal consist of, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is noise matrix; Y ^HThe associate matrix of expression observation signal Y, R _XThe covariance matrix of expression source signal matrix X, R _NThe covariance matrix of expression noise matrix N,

With

Covariance matrix between expression source signal and noise, and With

Be 0; σ ²Be the variance of noise matrix N, I _nBe n * n rank unit matrix;

Steps A 2, to determinant | λ I-XX ^H|=0 finds the solution, and obtains described covariance matrix R _YCharacteristic value { λ ₁, λ ₂..., λ _nAnd corresponding eigenvectors matrix A:A={a ₁, a ₂..., a _n, described characteristic value is that descending order is arranged;

Steps A 3, setting matrix D: D=diag ((λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²)), wherein, diag () is that diagonal element is by (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) matrix that forms, { (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) be the characteristic value of observation signal Y;

Steps A 4, obtain described albefaction matrix W according to described matrix D and matrix A, described albefaction matrix W is: W=D ^-1/2A ^H=[(λ ₁+ σ ²) ^-1/2a ₁, (λ ₂+ σ ²) ^-1/2a ₂..., (λ _n+ σ ²) ^-1/2a _n] ^H

In above-mentioned steps A1, the average of usually supposing noise matrix N is 0, and with the signal of source node broadcasting be incoherent, therefore, the covariance matrix between signal and noise equals 0, namely $R_{{\mathrm{XN}}^H}=E\left\{{\mathrm{XN}}^H\right\}=E\left\{X\right\}E\left\{N^H\right]=0,$ Similarly, $R_{{\mathrm{NX}}^H}=0,$ And σ ²Variance for additivity white Gaussian (AWGN) noise matrix N.In steps A 2, to determinant | λ I-XX ^H|=0 characteristic value that obtains after finding the solution is arranged according to order from big to small, n larger characteristic value { λ before getting in characteristic value ₁, λ ₂..., λ _nAnd the matrix A that forms of corresponding characteristic vector={ a ₁, a ₂..., a _n, simultaneously, the characteristic value that can obtain observation signal matrix Y according to the character of matrix is { (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²).

In above-mentioned steps 521, whitened signal Z is carried out analyzing and processing, obtaining separation matrix V can specifically comprise:

Step B1, according to described whitened signal Z, obtain the fourth order cumulant Q of described whitened signal Z _Z, and according to described fourth order cumulant Q _ZObtain described fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n}, according to described fourth order cumulant Q _ZFeature to obtaining characteristic set N _set: N _set={ λ _rM _r| 1≤r≤n}, wherein, λ _rBe characteristic value, M _rFor with λ _rThe matrix that corresponding characteristic vector forms, n is the number of observation signal, in the present embodiment, n is 2;

Step B2, by the associating diagonalization to described characteristic set N _setProcess, obtain described separation matrix V.

Wherein, in step B1, according to described fourth order cumulant Q _ZObtain fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n} comprises: with fourth order cumulant Q _ZForm n ²* n ²Matrix Q; Obtain characteristic value and the corresponding characteristic vector of matrix Q according to matrix Q, with front n larger characteristic value and corresponding characteristic vector composition characteristic to { λ _r, M _r| 1≤r≤n}.Particularly, if a random vector has zero-mean m ₀With the covariance matrix R of unit (can be also that the unit covariance matrix is multiplied by a normal value variances sigma again ²), claim that this random vector is albefaction, therefore the vector after albefaction is processed satisfies following formula:

$\left\{\begin{array}{c}{m}_0=0\\ R=I\end{array}\right.$

Wherein I is unit matrix.Generally, the covariance of establishing source signal matrix X is 1, i.e. E{XX ^H}=1, synchronous signal X ' is the signal after processing through albefaction, namely

I＝WR _X′W＝WKE[XX ^H]K ^HW ^H

＝WKK ^HW ^H

Obviously, there is unitary matrice U=WK, satisfies unitary matrice definition I=UU ^HSo, hybrid matrix K can be expressed as

K＝W ^-U＝W ^-[u ₁，...，u _n]

Matrix W herein ^-Represent the generalized inverse matrix of albefaction matrix W.

Processing through albefaction the signal Z that obtains is:

Z＝WY＝W(KX+N)＝VX+WN

It is linear that signal Z after albefaction remains.According to formula E=V ^HZ can obtain the expression formula of estimated matrix E:

E＝V ^HZ＝V ^HUX+V ^HWN

If U=V knows V by the unitary matrice definition ^HU=V ^HV=I, I herein has identical dimension with V.The signal that is mixed with the AWGN noise that estimated matrix E represents is equal to the signal of source signal through producing after certain phase shift, so has high-order intersection cumulant identically vanishing to set up.

Therefore, in the present embodiment, the method for fourth order cumulant is adopted in blind separation for the whitened signal Z that produces after processing through albefaction.The four-dimensional cumulant Q of definable whitened signal Z _ZFor:

$Q_z=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\underset{k=1}{\overset{n}{\mathrm{\Σ}}}\underset{l=1}{\overset{n}{\mathrm{\Σ}}}\mathrm{Cum}(z_i,z_j^{*},z_k,z_l^{*}),1\≤i,j,k,l\≤n$

By to described fourth order cumulant Q _zCarry out computing, described fourth order cumulant Q _zFor:

$Q_Z=E\left(z_i{z}_j^{*}{z}_l^{*}{z}_k\right)-E\left(z_i{z}_j^{*}\right)E\left(z_k{z}_l^{*}\right)-E\left(z_i{z}_l^{*}\right)E\left(z_k{z}_j^{*}\right)-E\left(z_i{z}_k\right)E\left(z_j^{*}{z}_l^{*}\right)=[Q_1,Q_2,...,Q_{n^4}]$

Wherein, z _j ^*Be z _jConjugation, z _l ^*Be z _lConjugation, i, l, k ∈ [1, n] is the subscript of observation signal.

As can be known, Q _ZIn contain n ⁴Individual value is according to this fourth order cumulant $Q_Z=[Q_1,Q_2,...,Q_{n^4}]$ , with described fourth order cumulant Q _ZThe n that comprises ⁴Individual value is mapped to n ²* n ²Matrix Q, described matrix Q is:

Q finds the solution to matrix, obtains characteristic value and the corresponding characteristic vector of matrix Q, and with the characteristic value that obtains by from big to small order sequence, get wherein before n larger characteristic value, with n ²Individual characteristic vector consists of the matrix on a n * n rank, obtains Q _ZFeature to { λ _r, M _r| 1≤r≤n}, thus eigenmatrix set N obtained _set:

N _set＝{λ _rM _r|1≤r≤n}

Wherein, N _setThe set that is formed by n matrix.

In above-mentioned steps B2, by uniting diagonalization to characteristic set N _setProcess, obtain separation matrix V and comprise: according to described characteristic set N _setTarget setting function C (V, N), described target function C (V, N) is:

$C(V,N)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{l=1}{\overset{n}{\mathrm{\Σ}}}\underset{k=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{Cum}(z_i,z_i^{*},z_l,z_k)\right|}^2=\underset{r=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{diag}\left(V^H{N}_{r}V\right)\right|}^2$

Wherein, set $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\′}& b_r^{\′}\\ c_r^{\′}& d_r^{\′}\end{array}\right],$ Diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V forms, a ' _r, b ' _r, c ' _r, d ' _rV ^HN _rThe coefficient of V, $N_r=\left[\begin{array}{cc}{a}_r& b_r\\ c_r& d_r\end{array}\right]$ Be characteristic set N _setIn an element, i, l, k ∈ [1, n] is the subscript of observation signal; Target function C (V, N) is carried out iteration optimization process, obtain separation matrix V.Wherein, target function C (V, N) is carried out iteration optimization process, obtain separation matrix V and comprise: set matrix T according to target function C (V, N), matrix T is:

$T=\underset{r}{\mathrm{\Σ}}{|a_r^{\′}-d_r^{\′}|}^2=P^T{G}^H\mathrm{GP}=P^T\mathrm{Re}\left(G^{H}G\right)P$

Wherein, a ' _r-d ' _r=(a _r-d _r) cos2 α+(b _r-c _r) sin2 α cos β+j (c _r-b _r) sin2 α sin β=P ^Tg _r, P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TMatrix Re (G ^HG) characteristic value characteristic of correspondence vector, g _r=[a _r-d _r, b _r+ c _r, j (c _r-b _r)] ^T, r=1 ..., n, G=[g ₁, g ₂..., g _n] ^T, Re () represents real; Obtain Re (G ^HG) the eigenvalue of maximum characteristic of correspondence of matrix vector, and according to this eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TObtain corresponding α and β; If Δ V ^H, Δ V has the structure of hermitian, and $\mathrm{\ΔV}=\left[\begin{array}{cc}\cos \mathrm{\α}& -e^{\mathrm{j\β}}\sin \mathrm{\β}\\ e^{-\mathrm{j\β}}\sin \mathrm{\α}& \cos \mathrm{\α}\end{array}\right],$ Carry out according to described α and β the updating value V that interative computation obtains separation matrix _new: V _new=V Δ V; Updating value V according to described separation matrix _newUpgrade described eigenmatrix set N _setIn element N _r: N _r=Δ V ^HN _rΔ V; Judge whether α satisfies the iteration stopping condition, if the updating value of the separation matrix of this moment is described separation matrix V.In addition, described according to also comprising before target function C (V, N) setting matrix T: the described separation matrix V=I of initialization _nSet described iteration stopping condition, described iteration stopping condition is | sin α | and＞1/100/ (n) ^1/2

Particularly, according to the characteristic set N of above-mentioned acquisition _set, with N _setIn an element representation be N _r:

$N_r=\left[\begin{array}{cc}{a}_r& b_r\\ c_r& d_r\end{array}\right]$ r＝1，...，n

And target setting function C (V, N): $C(V,N)=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{l=1}{\overset{n}{\mathrm{\Σ}}}\underset{k=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{Cum}(z_i,z_i^{*},z_l,z_k)\right|}^2=\underset{r=1}{\overset{n}{\mathrm{\Σ}}}{\left|\mathrm{diag}\left(V^H{N}_{r}V\right)\right|}^2,$ And V ^HN _rV has expression-form: $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\′}& b_r^{\′}\\ c_r^{\′}& d_r^{\′}\end{array}\right],$ Wherein, diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V forms, a ' _r, b ' _r, c ' _r, d ' _rV ^HN _rThe coefficient of V.

The iteration optimization process of target function C (V, N) just is equivalent to finds out α and β makes ∑ _r| a ' _r| ²+ | d ' _r| ²Obtain maximum.According to 2 (| a ' _r| ²+ | d ' _r| ²)=| a ' _r-d ' _r| ²+ | a ' _r+ d ' _r| ²And N ' _r=V ^HN _rThe characteristic that after the V unitary transformation, matrix trace remains unchanged as can be known, to ∑ _r| a _r| ²+ | d _r| ²Maximizing just is equivalent to ∑ _r| a ' _r| ²+ | d ' _r| ²Maximizing, and then be equivalent to maximizing: $T=\underset{r}{\mathrm{\Σ}}{|a_r^{\′}-d_r^{\′}|}^2.$

By above-mentioned formula N ' _r=V ^HN _rV, by calculating as can be known:

a′ _r-d ' _r=(a _r-d _r) cos2 α+(b _r-c _r) sin2 α cos β+j (c _r-b _r) sin2 α sin β is for ease of understanding and explanation, setting is following auxiliary vectorial:

P＝[cos2α，sin2αcosβ，sin2αsinβ] ^T

g _r＝[a _r-d _r，b _r+c _r，j(c _r-b _r)] ^T

G＝[g ₁，g ₂，…，g _n] ^T

Formula a ' _r-d ' _r=(a _r-d _r) cos2 α+(b _r-c _r) sin2 α cos β+j (c _r-b _r) sin2 α sin β can be expressed as:

a′ _r-d′ _r＝P ^Tg _r

So have:

$T=\underset{r}{\mathrm{\Σ}}{|a_r^{\′}-d_r^{\′}|}^2=P^T{G}^H\mathrm{GP}=P^T\mathrm{re}\left(G^{H}G\right)P$

If Δ V ^HΔ V has the structure of hermitian (Hermitian), and Δ V can be made as:

$\mathrm{\ΔV}=\left[\begin{array}{cc}\cos \mathrm{\α}& -e^{\mathrm{j\β}}\sin \mathrm{\β}\\ e^{-\mathrm{j\β}}\sin \mathrm{\α}& \cos \mathrm{\α}\end{array}\right]$

Infinitely to approach with real source signal in order making through the estimated value of the source signal of the observation signal resulting separation that mixes, need to enter iterative process, iterative process each time is as long as calculate Re (G ^HG) get final product.Wherein, iterative process is as follows:

At first carry out iteration initialization, at the iterative process initial phase, initialization separation matrix V is: V=I _n, and set the iteration stopping condition, described iteration stopping condition is | sin α |＞1/100/ (n) ^1/2Then enter iterative process, in iterative process each time, all need the characteristic value of compute matrix T, and get wherein maximum characteristic value and corresponding characteristic vector matrix G is upgraded, in iterative process, can be constantly to eigenmatrix set N _setIn each element Nr upgrade, its renewal process is as follows:

V _new＝V·ΔV

N _r＝ΔV ^HN _rΔV

In the present embodiment, for to eigenmatrix set N _setCarry out diagonalization, will get maximum and as criterion, diagonal entry quadratic sum in objective function matrix be carried out iterative computation, and in the situation that the angle [alpha] that twice adjacent calculation obtains is more or less the same, stop iterative process, and then obtain separation matrix V.

In the present embodiment, after obtaining separation matrix V, utilize the V=U=WK that concerns between matrix W and matrix K, can obtain the expression formula of matrix K: K=W ^-U=W ^-V。

At last, utilize relational expression E=V ^HZ can get:

$\left[\begin{array}{c}{e}_1\left[m\right]\\ e_2\left[m\right]\end{array}\right]=V^H\left[\begin{array}{c}{z}_1\left[m\right]\\ z_2\left[m\right]\end{array}\right]$

At this moment, can obtain source signal x ₁[m], x ₂The estimated value e that [m] is corresponding ₁[m], e ₂[m], and with this estimated value as the source signal value, simultaneously can be to e ₁[m], e ₂[m] decodes, and obtains source signal x ₁[m], x ₂The information such as [m] and source node sign, and according to the information such as source node sign are sorted to source signal.

Need to prove, owing to can observation signal (mixed signal that receives) being separated the estimated value that obtains source signal by the physical layer encodes processing method, can obtain the source node sign after simultaneously estimated value being decoded, therefore can sort to source signal, overcome the source signal that obtains in the ICA method and had the fuzzy technological deficiency of order.In technique scheme of the present invention, source node can be for more than three or three, when the separation method of its method for transmitting signals and mixed signal and source node are two roughly the same.

Technical solution of the present invention is by adopting mixed signal to carry out the transmission of signal, the time slot that makes the signal transmission take reduces, therefore, saved the time of network node busy channel, improved the throughput of network node, effectively improve the integrated communication capacity of network, promoted network bandwidth utilization factor; Simultaneously, in technical solution of the present invention, by adopting the ICA isolation technics that mixed signal is processed, the source signal of acquisition accurately, reliably.

It should be noted that at last: above embodiment is only in order to technical scheme of the present invention to be described but not be limited, although with reference to preferred embodiment, the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be modified or be equal to replacement technical scheme of the present invention, and these modifications or be equal to replacement and also can not make amended technical scheme break away from the spirit and scope of technical solution of the present invention.

Claims (9)

1. a physical layer network code processing method, is characterized in that, comprising:

The first source node broadcasting first signal, the second source node broadcasting secondary signal;

Via node receives the relaying mixed signal, and described relaying mixed signal is that the signal that arrives described via node place after making an uproar is mixed, added to described first signal and secondary signal process; Destination node receives the first mixed signal, and described the first mixed signal is that the signal that arrives described destination node place after making an uproar is mixed, added to described first signal and secondary signal process;

The described relaying mixed signal of described via node broadcasting;

Described destination node receives the second mixed signal, and described the second mixed signal is described relaying mixed signal through adding the signal that arrives described destination node place after making an uproar;

Described destination node obtains the estimated value of first signal and secondary signal according to described the first mixed signal and the second mixed signal, specifically comprise:

With described the first mixed signal and the second mixed signal in conjunction with and obtain the observation signal Y of described destination node;

By Independent Component Analysis, described observation signal Y is processed, obtain the estimated value of described first signal and secondary signal.

2. physical layer network code processing method according to claim 1, is characterized in that, described described observation signal Y the processing by Independent Component Analysis comprises:

Described observation signal Y is carried out albefaction process, obtain whitened signal Z;

Described whitened signal Z is carried out analyzing and processing, obtain separation matrix V;

Obtain to comprise according to described separation matrix V and whitened signal Z the estimated matrix E:E=V that the estimated value by described first signal and secondary signal forms ^HZ。

3. physical layer network code processing method according to claim 2, is characterized in that, describedly described observation signal Y is carried out albefaction processes, and obtains whitened signal Z and comprise:

Obtain covariance matrix R according to described observation signal Y _Y, and according to described covariance matrix R _YObtain the albefaction matrix W;

By described albefaction matrix W, described observation signal Y is carried out albefaction and process, obtain whitened signal Z:Z=WY.

4. physical layer network code processing method according to claim 3, is characterized in that, and is described according to described observation signal Y acquisition covariance matrix R _Y, and according to described covariance matrix R _YObtaining the albefaction matrix W comprises:

Obtain the covariance matrix R of described observation signal Y according to described observation signal Y _Y, described covariance matrix R _YFor:

Wherein, Y=KX+N, X are the source signal matrix that first signal and secondary signal consist of, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is noise matrix; Y ^HThe associate matrix of expression observation signal Y, R _XThe covariance matrix of expression source signal matrix X, R _NThe covariance matrix of expression noise matrix N,

With

Covariance matrix between expression source signal and noise, and

With Be 0; σ ²Be the variance of noise matrix N, I _nBe n * n rank unit matrix, n is the number of observation signal;

To determinant | λ I-XX ^H|=0 finds the solution, and obtains described covariance matrix R _YCharacteristic value { λ ₁, λ ₂..., λ _nAnd corresponding eigenvectors matrix A:A={a ₁, a ₂..., a _n, described characteristic value is that descending order is arranged;

Set matrix D: D=diag[(λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²)], wherein, diag () is that diagonal element is by (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) matrix that forms, { (λ ₁+ σ ²), (λ ₂+ σ ²) ..., (λ _n+ σ ²) be the characteristic value of observation signal Y;

Obtain described albefaction matrix W according to described matrix D and matrix A, described albefaction matrix W is:

W＝D ^-1/2A ^H＝[(λ ₁+σ ²) ^-1/2a ₁，(λ ₂+σ ₂) ^-1/2a ₂，…，(λ _n+σ ²) ^-1/2a _n] ^H。

5. physical layer network code processing method according to claim 2, is characterized in that, described described whitened signal Z carried out analyzing and processing, obtains separation matrix V and comprise:

According to described whitened signal Z, obtain the fourth order cumulant Q of described whitened signal Z _Z, and according to described fourth order cumulant Q _ZObtain described fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n}, according to described fourth order cumulant Q _ZFeature to obtaining characteristic set N _set: N _set={ λ _rM _r| 1≤r≤n}, wherein, λ _rBe characteristic value, M _rFor with λ _rThe matrix that corresponding characteristic vector forms, n is the number of observation signal;

By uniting diagonalization to described characteristic set N _setProcess, obtain described separation matrix V.

6. physical layer network code processing method according to claim 5, is characterized in that, and is described according to described fourth order cumulant Q _ZObtain described fourth order cumulant Q _ZFeature to { λ _r, M _r| 1≤r≤n} comprises:

With described fourth order cumulant Q _ZForm n ²* n ²Matrix Q;

Obtain characteristic value and the corresponding characteristic vector of described matrix Q according to described matrix Q, front n larger characteristic value and corresponding characteristic vector are formed described feature to { λ _r, M _r| 1≤r≤n}.

7. physical layer network code processing method according to claim 5, is characterized in that, the described associating diagonalization that passes through is to described characteristic set N _setProcess, obtain described separation matrix V and comprise:

According to described characteristic set N _setTarget setting function C (V, N), described target function C (V, N) is:

Wherein, set Diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V forms, a ' _r, b ' _r, c ' _r, d ' _rV ^HN _rThe coefficient of V, Be characteristic set N _setIn an element, i, l, k ∈ [1, n] is the subscript of observation signal; z _iBe i observation signal, z _lBe l observation signal, z _kBe k observation signal;

Described target function C (V, N) is carried out iteration optimization process, obtain described separation matrix V.

8. physical layer network code processing method according to claim 7, is characterized in that, describedly described target function C (V, N) is carried out iteration optimization processes, and obtains described separation matrix V and comprise:

Set matrix T according to target function C (V, N), matrix T is:

Wherein,

P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TMatrix Re (G ^HG) characteristic value characteristic of correspondence vector, g _r=[a _r-d _r, b _r+ c _r, j (c _r-b _r)] ^T, r=1 ..., n, G=[g ₁, g ₂..., g _n] ^T, Re () represents real;

Obtain Re (G ^HG) the eigenvalue of maximum characteristic of correspondence of matrix vector, and according to described eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos2 α, sin2 α cos β, sin2 α sin β] ^TObtain corresponding α and β;

If Δ V ^H, Δ V has the structure of hermitian, and

Carry out according to described α and β the updating value V that interative computation obtains separation matrix _new: V _new=V Δ V;

Updating value V according to described separation matrix _newUpgrade described eigenmatrix set N _setIn element N _r: N _r=Δ V ^HN _rΔ V;

Judge whether α satisfies the iteration stopping condition, if the updating value of the separation matrix of this moment is described separation matrix V.

9. physical layer network code processing method according to claim 8, is characterized in that, and is described according to also comprising before target function C (V, N) setting matrix T:

The described separation matrix V=I of initialization _n

Set described iteration stopping condition, described iteration stopping condition is | sin α | and＞1/100/ (n) ^1/2

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