CN101478374A - 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 the wireless network has mobility and portability, make that the establishment of Wi-Fi is convenient, flexibly, wireless network has obtained general application.The link of wireless network has broadcast characteristic, and promptly the node in the wireless network can be to other a plurality of node broadcasts information, and same, the node in the wireless network also can receive the information from other a plurality of nodes.Because the broadcast characteristic of node, if the interior at one time broadcast message of a plurality of nodes in the network, can in the free space of propagating, mix mutually between a plurality of signals that then a plurality of node broadcasts are gone out, the mixing of signal can cause to produce between the signal and disturb, and the information that causes receiving node to receive is inaccurate maybe can't to receive required information.Therefore, be the generation that avoids interference, the transmission of Information method generally all adopts and sends signal in succession and realize transmission of Information in the prior art.

Fig. 1 is the structural representation of message transmission in the prior art wireless network; Fig. 2 is the sequential chart that signal transmits in the information transferring method in the prior art wireless network.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 message transmission to destination node D.As shown in Figure 2, in the 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 broadcast that the source node S 1 that observes is broadcasted, and receives the information that via node R broadcasts 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 broadcast that the source node S 2 that observes is broadcasted, and receives the information that via node R broadcasts by destination node D, and destination node D obtains the information of source node S 2.As can be seen, in the prior art, two source nodes finishing once that communication needs 4 time slots at least when same destination node transmission information, communicate by letter if having between plural source node and the destination node, and the time slot that then needs will be more.

As can be seen, in the information transferring method, disturb in the prior art wireless network for avoiding signal, improve the accuracy of message transmission, when communicating by letter between multiple source node and the same destination node, the time slot of finishing primary information transmission needs is too much, make that the network whole volume is 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 interference that the back 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:

First source node is broadcasted first signal, second source node broadcasting secondary signal;

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

Described via node is broadcasted described relaying mixed signal;

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

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

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

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

By the independent component analysis method described observation signal Y is handled, obtain the estimated value of described first signal and secondary signal.

Described described observation signal Y the processing by the independent component analysis method comprises:

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

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

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

Describedly described observation signal Y carried out albefaction handle, 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 handle, 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 constitute, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is a 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 the 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 formed, { (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 is formed, n is the number of observation signal;

By uniting diagonalization to described characteristic set N _SetHandle, 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, preceding n big 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 _SetHandle, obtain described separation matrix V and comprise:

According to described characteristic set N _SetThe target 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 ^HThe matrix that the characteristic value of NrV is formed,

Be V ^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;

(V N) carries out iteration optimization and handles, and obtains described separation matrix V to described target function C.

Described to described target function C (V N) carries out iteration optimization and handles, and obtains described separation matrix V and comprises:

According to target function C (V N) sets matrix T, and 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, $a_r^{\&prime;}-d_r^{\&prime;}=(a_r-d_r)\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&alpha;}+(b_r-c_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\cos \mathrm{\&beta;}+j(c_r-b_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\sin \mathrm{\&beta;}=P^T{g}_r,$ P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TBe matrix 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 vector of matrix, and according to described eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TObtain corresponding α and β;

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

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

The described separation matrix V=I of initialization _n

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

In the technical solution of the present invention, the mixed signal transmission is adopted in signal transmission between source node and the 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 utilance; Simultaneously, in the technical solution of the present invention by adopting the ICA isolation technics that the mixed signal that destination node receives is handled, make mixed signal separating resulting accurately, reliable.

Description of drawings

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

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

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

Fig. 4 is the sequential chart of signal transmission in the 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 carries out the schematic flow sheet of separating treatment to mixed signal for destination node in the physical layer network code processing method of the present invention;

The schematic flow sheet that Fig. 7 handles observation signal for the present invention.

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 the physical layer network code processing method of the present invention; Fig. 4 is the sequential chart of signal transmission in the physical layer network code processing method of the present invention.Embodiment of the invention technical scheme can be applicable in the existing wireless network, different with method for transmitting signals in the prior art is, signal is to transmit with hybrid mode in the embodiment of the invention, the signal that destination node receives is that the multiple source node signal is 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.This method comprises:

Step 1, first source node are broadcasted first signal, 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 the back of making an uproar arrives described via node place is mixed, added to described first signal and secondary signal process; Destination node receives first mixed signal, and described first mixed signal is that the signal that the back of making an uproar arrives described destination node place is mixed, added to described first signal and secondary signal process;

Step 3, described via node are broadcasted described relaying mixed signal;

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

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

In the present embodiment, as shown in Figure 4, at the first time slot T ₁, first source node S ₁With second source node S ₂The signal broadcasting that needs send is gone out 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 via node R and destination node D respectively through the mixed signal of mixing, adding after making an uproar; Simultaneously, via node R and destination node D receive the relaying mixed signal and first mixed signal respectively; 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 second mixed signal after making an uproar in the free space transmission.So far, first source node S ₁With second source node S ₂And a signal transmission between the destination node D is finished, destination node D carries out separating treatment to first mixed signal and 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 first source node S ₁With second source node S ₂Send to the information of destination node.In the present embodiment technical scheme, source node also can be more than three or three, and correspondingly, the signal that purpose receives mixes, adds the mixed signal after making an uproar for the multiple source node signal, destination node can be separated it equally, obtains the estimated value of the broadcast singal of each source node.

Particularly, first mixed signal and second mixed signal that destination node can adopt Blind Signal Separation (Blind SignalSeparation is called for short BSS) interface differential technique to receive in the present embodiment 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 under the situation of 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 the primary signal that source node sends by the mixed signal that receives is carried out separating treatment.As can be seen, can realize mixed signal is separated by the BSS technology, make the multiple source node can transmit a signal to destination node simultaneously, be that signal can carry out transmission of Information with the form of mixed signal, it is few to make that each source node and destination node are carried out the timeslot number of signal transmission, therefore, time and channel that the signal transmission takies reduce accordingly, improve the signal transmitting speed, effectively improved the whole message capacity of network, promoted utilization of network bandwidth.

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

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

Step 52, described observation signal Y is handled, obtain the estimated value of described first signal and secondary signal by the independent component analysis method.

In the above-mentioned steps 51, destination node can be handled first mixed signal and 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 the 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 first source node S ₁First signal of broadcasting, x ₂[m] is second source node S ₂The secondary signal of broadcasting, at this, also can be with x ₁[m], x ₂First source node S that [m] obtains according to the ICA method as destination node ₁With 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 in spatial transmission through decline, multipath and the phase shift of channel, 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 fading coefficient on channel, and node j is to the distance dependent between the node i, φ is the phase shift that signal produces on channel.

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

$x_1^{\&prime;}\left[m\right]=k_{{\mathrm{rs}}_1}{A}_{s_1}\left[m\right]e^{i({\mathrm{\&theta;s}}_1\left[m\right]+{\mathrm{\&phi;}}_1)}$

$x_2^{\&prime;}\left[m\right]=k_{{\mathrm{rs}}_2}{A}_{s_2}\left[m\right]e^{i({\mathrm{\&theta;s}}_2\left[m\right]+{\mathrm{\&phi;}}_2)}$

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

$y_r\left[m\right]=x_1^{\&prime;}\left[m\right]+x_2^{\&prime;}{\left[m\right]+n_r\left[m\right]=k}_{{\mathrm{rs}}_1}{A}_{s_1}\left[m\right]e^{i({\mathrm{\&theta;s}}_1\left[m\right]+{\mathrm{\&phi;}}_1)}+k_{{\mathrm{rs}}_2}{A}_{s_2}\left[m\right]e^{i({\mathrm{\&theta;s}}_2\left[m\right]+{\mathrm{\&phi;}}_2)}+n_r\left[m\right]$

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

Similarly, first mixed signal that receives of destination node is:

$y_{d_1}\left[m\right]=x_1^{\&prime;\&prime;}\left[m\right]+x_2^{\&prime;\&prime;}{\left[m\right]+n_1\left[m\right]=k}_{{\mathrm{ds}}_1}{A}_{s_1}\left[m\right]e^{i({\mathrm{\&theta;s}}_1\left[m\right]+{\mathrm{\&phi;}}_1^{\&prime;})}+k_{{\mathrm{ds}}_2}{A}_{s_2}\left[m\right]e^{i({\mathrm{\&theta;s}}_2\left[m\right]+{\mathrm{\&phi;}}_2^{\&prime;})}+n_1\left[m\right]$

Wherein,

Be first mixed signal, $x_1^{\&prime;\&prime;}\left[m\right]=k_{{\mathrm{ds}}_1}{A}_{s_1}\left[m\right]e^{i({\mathrm{\&theta;s}}_1\left[m\right]+{\mathrm{\&phi;}}_1^{\&prime;})}$ It is first source node S ₁The first signal x of broadcasting ₁Expression when [m] arrives destination node D, $x_2^{\&prime;\&prime;}\left[m\right]=k_{{\mathrm{ds}}_2}{A}_{s_2}\left[m\right]e^{i({\mathrm{\&theta;s}}_2\left[m\right]+{\mathrm{\&phi;}}_2^{\&prime;})}$ It is 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 the 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 then second mixed signal that receives of destination node D is:

$y_{d_2}\left[m\right]=k_{\mathrm{dr}}(x_1^{\&prime;}\left[m\right]+x_2^{\&prime;}\left[m\right])e^{i{\mathrm{\&phi;}}_r}+{\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">n</figure-callout>}}_2^{\&prime;}\left[m\right]+n_r\left[m\right]$

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

Wherein, Be second mixed signal, $n_2\left[m\right]=n_r\left[m\right]+{\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">n</figure-callout>}}_2^{\&prime;}\left[m\right]$ For the source node signal arrives the noise cancellation signal that adds in the destination node process by via node,

Be the noise cancellation signal that adds in the 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, $K=\left[\begin{array}{cc}{k}_{{\mathrm{ds}}_1}{e}^{{\mathrm{i\&phi;}}_{{\mathrm{ds}}_1}}& k_{{\mathrm{ds}}_2}{e}^{{\mathrm{i\&phi;}}_{{\mathrm{ds}}_2}}\\ k_{\mathrm{dr}}{k}_{{\mathrm{rs}}_1}{e}^{i({\mathrm{\&phi;}}_{\mathrm{<figure-callout\; id="1"\; label="rs"\; filenames="A200910077201E00242.png"\; state="\{\{state\}\}">rs</figure-callout>}1}+{\mathrm{\&phi;}}_{\mathrm{dr}})}& k_{\mathrm{dr}}{k}_{\mathrm{rs}}{e}^{i({\mathrm{\&phi;}}_{{\mathrm{<figure-callout\; id="2"\; label="rs"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">rs</figure-callout>}}_2}+{\mathrm{\&phi;}}_{\mathrm{dr}})}\end{array}\right]$ Be the hybrid matrix of signal amplitude and phase fading coefficient on channel, $N=\left[\begin{array}{c}{n}_1\left[m\right]\\ n_2\left[m\right]\end{array}\right]$ For signal adds the matrix of making an uproar on channel.

As can be seen, only require that solving hybrid matrix K just can utilize above-mentioned formula to solve X, can obtain first source node S ₁The first signal value x of broadcasting ₁[m] and second source node S ₂The secondary signal value x of broadcasting ₂[m].

Particularly, the schematic flow sheet observation signal handled for the present invention of Fig. 7.On the basis of above-mentioned Fig. 6 technical scheme, in order to solve hybrid matrix K, 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 first source node S ₁With 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 handle, 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 the estimated matrix E:E=V that forms by the estimated value of described first signal and secondary signal according to described separation matrix V and whitened signal Z ^HZ.

In the above-mentioned steps 520, observation signal Y is carried out albefaction handle, 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 handle, 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:

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

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

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

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

$={\mathrm{KR}}_X{K}^H+{\mathrm{\&sigma;}}^2{I}_n$

Wherein, Y=KX+N, X are the source signal matrix that first signal and secondary signal constitute, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is a 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 the 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 formed, { (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

Among the above-mentioned steps A1, the average of supposing noise matrix N usually is 0, and with the signal of source node broadcasting be incoherent, therefore, the covariance matrix between signal and the noise equals 0, promptly $R_{{\mathrm{XN}}^H}=E\left\{{\mathrm{XN}}^H\right\}=E\left\{X\right\}E\left\{N^H\right\}=0$ , similarly, $R_{{\mathrm{NX}}^H}=0,$ And σ ²Variance for additivity white Gaussian (AWGN) noise matrix N.In the 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 big characteristic value { λ before then getting in characteristic value ₁, λ ₂..., λ _nAnd matrix A={ a of forming of corresponding characteristic vector 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 the 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 _zThe feature that obtains described fourth order cumulant Qz is 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 is formed, n is the number of observation signal, n is 2 in the present embodiment;

Step B2, by the associating diagonalization to described characteristic set N _SetHandle, 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 preceding n big 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 (also can be that the unit covariance matrix is multiplied by a normal value variances sigma again ²), claim that then this random vector is albefaction, therefore the vector after albefaction is handled satisfies following formula:

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

Wherein I is a 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 handling through albefaction, promptly

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.

Handling the signal Z that obtains through albefaction is:

Z＝WY＝W(KX+N)＝VX+WN

It is linear that signal z after the 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 the certain phase shift, so then 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 handling through albefaction.The four-dimensional cumulant Q of definable whitened signal Z _zFor:

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

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

$Q_Z=E\left(z_i{z}_j^{*}{z}_l^{*}{z}_k\right)-E\left(z_i{z}_j^{*}\right)E\left(z_k{z}_l^{*}\right)-E\left(z_i{z}_l^{*}\right)E\left(z_k{z}_j^{*}\right)-E\left(z_i{z}_k\right)E\left(z_j^{*}{z}_l^{*}\right)=[{\mathrm{<figure-callout\; id="1"\; label="Q"\; filenames="A200910077201E00242.png"\; state="\{\{state\}\}">Q</figure-callout>}}_1,{\mathrm{<figure-callout\; id="2"\; label="Q"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">Q</figure-callout>}}_2,\&CenterDot;\&CenterDot;\&CenterDot;,Q_{n^4}]$

Wherein,

Be z _jConjugation,

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 $Q_Z=[{\mathrm{<figure-callout\; id="1"\; label="Q"\; filenames="A200910077201E00242.png"\; state="\{\{state\}\}">Q</figure-callout>}}_1,{\mathrm{<figure-callout\; id="2"\; label="Q"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">Q</figure-callout>}}_2,\&CenterDot;\&CenterDot;\&CenterDot;,Q_{n^4}],$ 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 rank order, get wherein before n bigger 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 of forming by n matrix.

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

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

Wherein, set $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\&prime;}& b_r^{\&prime;}\\ c_r^{\&prime;}& d_r^{\&prime;}\end{array}\right],$ Diag () is by V for diagonal element ^HThe matrix that the characteristic value of NrV is formed,

Be V ^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; (V N) carries out iteration optimization and handles, and obtains separation matrix V to target function C.Wherein, to target function C (V N) carries out iteration optimization and handles, and obtains separation matrix V and comprises: according to target function C (V N) sets matrix T, and matrix T is:

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

Wherein, $a_r^{\&prime;}-d_r^{\&prime;}=(a_r-d_r)\cos 2\mathrm{\&alpha;}+(b_r-c_r)\sin 2\mathrm{\&alpha;}\cos \mathrm{\&beta;}+j(c_r-b_r)\sin 2\mathrm{\&alpha;}\sin \mathrm{\&beta;}=P^T{g}_r,$ P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TBe matrix 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 vector of matrix, and according to this eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TObtain corresponding α and β; If Δ V ^H, Δ V has the structure of hermitian, and $\mathrm{\&Delta;V}=\left[\begin{array}{cc}\cos \mathrm{\&alpha;}& -e^{\mathrm{j\&beta;}}\sin \mathrm{\&beta;}\\ e^{-\mathrm{j\&beta;}}\sin \mathrm{\&alpha;}& \cos \mathrm{\&alpha;}\end{array}\right],$ Carry out the updating value V that interative computation obtains separation matrix according to described α and β _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 then the updating value of Ci Shi separation matrix is described separation matrix V.It is in addition, described that (V N) sets matrix T and also comprises before: the described separation matrix V=I of initialization according to target function C _nSet described iteration stopping condition, described iteration stopping condition is | sin α | 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 the target setting function C (V, N): $C(V,N)=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}\underset{l=1}{\overset{n}{\mathrm{\&Sigma;}}}\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\mathrm{Cum}(z_i,z_i^{*},z_l,z_k)\right|}^2=\underset{r=1}{\overset{n}{\mathrm{\&Sigma;}}}{\left|\mathrm{diag}\left(V^H{N}_{r}V\right)\right|}^2,$ And V ^HN _rV has expression-form: $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\&prime;}& b_r^{\&prime;}\\ c_r^{\&prime;}& d_r^{\&prime;}\end{array}\right],$ Wherein, diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V is formed,

Be V ^HN _rThe coefficient of V.

(V, iteration optimization process N) just is equivalent to be found out α and β and makes to target function C

Obtain maximum.According to $2({\left|a_r^{\&prime;}\right|}^2+{\left|d_r^{\&prime;}\right|}^2)={|a_r^{\&prime;}-d_r^{\&prime;}|}^2+{|a_r^{\&prime;}+d_r^{\&prime;}|}^2$ With $N_r^{\&prime;}=V^H{N}_{r}V$ The characteristic that matrix trace remains unchanged after the unitary transformation as can be known, to ∑ _r| a _r| ²+ | d _r| ²Maximizing, it is right just to be equivalent to ${\mathrm{\&Sigma;}}_r{\left|a_r^{\&prime;}\right|}^2+{\left|d_r^{\&prime;}\right|}^2$ Maximizing, and then be equivalent to maximizing: $T=\underset{r}{\mathrm{\&Sigma;}}{|a_r^{\&prime;}-d_r^{\&prime;}|}^2.$

By above-mentioned formula $N_r^{\&prime;}=V^H{N}_{r}V,$ By calculating as can be known:

$a_r^{\&prime;}-d_r^{\&prime;}=(a_r-d_r)\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&alpha;}+(b_r-c_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\cos \mathrm{\&beta;}+j(c_r-b_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\sin \mathrm{\&beta;}$

For ease of understanding and explaining, set following auxiliary vector:

P＝[cos?2α，sin?2α?cos?β，sin?2α?sin?β] ^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 then $a_r^{\&prime;}-d_r^{\&prime;}=(a_r-d_r)\mathrm{<figure-callout\; id="2"\; label="cos"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">cos</figure-callout>}2\mathrm{\&alpha;}+(b_r-c_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\cos \mathrm{\&beta;}+j(c_r-b_r)\mathrm{<figure-callout\; id="2"\; label="sin"\; filenames="A200910077201E00233.png,A200910077201E00242.png"\; state="\{\{state\}\}">sin</figure-callout>}2\mathrm{\&alpha;}\sin \mathrm{\&beta;}$ Can be expressed as:

$a_r^{\&prime;}-d_r^{\&prime;}=P^T{g}_r$

So then have:

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

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

$\mathrm{\&Delta;V}=\left[\begin{array}{cc}\cos \mathrm{\&alpha;}& -e^{\mathrm{j\&beta;}}\sin \mathrm{\&beta;}\\ e^{-\mathrm{j\&beta;}}\sin \mathrm{\&alpha;}& \cos \mathrm{\&alpha;}\end{array}\right]$

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) ^1/2Enter iterative process then, in iterative process each time, all need the characteristic value of compute matrix T, and get wherein maximum characteristic value and corresponding characteristic vector and come matrix G is upgraded, in the iterative process, can be constantly to eigenmatrix set N _SetIn each element N _rUpgrade, its renewal process is as follows:

V _new＝V·ΔV

N _r＝ΔV ^H?N _rΔV

In the present embodiment, for eigenmatrix is gathered N _SetCarry out diagonalization, will get maximum and diagonal entry quadratic sum in the target function matrix be carried out iterative computation, and under 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 as criterion.

In the present embodiment, obtain after the separation matrix V, utilize the V=U=WK that concerns between matrix W and the 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 ₂Information such as [m] and source node sign, and according to information such as source node sign are sorted to source signal.

Need to prove, owing to can separate the estimated value that obtains source signal to observation signal (mixed signal that receives) 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 the 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 carried out the transmission of signal by adopting mixed 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 utilance; Simultaneously, by adopting the ICA isolation technics that mixed signal is handled, the source signal of acquisition accurately, reliably in the technical solution of the present invention.

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 limit it, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that: it still can make amendment 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 (10)

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

First source node is broadcasted first signal, second source node broadcasting secondary signal;

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

Described via node is broadcasted described relaying mixed signal;

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

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

2, physical layer network code processing method according to claim 1 is characterized in that, described destination node comprises according to the estimated value that described first mixed signal and second mixed signal obtain first signal and secondary signal:

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

By the independent component analysis method described observation signal Y is handled, obtain the estimated value of described first signal and secondary signal.

3, physical layer network code processing method according to claim 2 is characterized in that, described described observation signal Y the processing by the independent component analysis method comprises:

Described observation signal Y is carried out albefaction handle, 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 by described first signal and secondary signal

The estimated matrix E:E=V that forms of estimated value ^HZ.

4, physical layer network code processing method according to claim 3 is characterized in that, describedly described observation signal Y is carried out albefaction handles, and obtains whitened signal z and comprises:

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 handle, obtain whitened signal z:Z=WY.

5, physical layer network code processing method according to claim 4 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:

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

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

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

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

$={\mathrm{KR}}_X{K}^H+{\mathrm{\&sigma;}}^2{I}_n$

Wherein, Y=KX+N, X are the source signal matrix that first signal and secondary signal constitute, and K is the hybrid matrix of signal amplitude and phase fading coefficient on channel, and N is a 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 the 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 formed, { (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

6, physical layer network code processing method according to claim 3 is characterized in that, described described whitened signal Z is carried out analyzing and processing, obtains separation matrix V and comprises:

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 is formed, n is the number of observation signal;

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

7, physical layer network code processing method according to claim 6 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, preceding n big characteristic value and corresponding characteristic vector are formed described feature to { λ _r, M _r| 1≤r≤n}.

8, physical layer network code processing method according to claim 6 is characterized in that, the described associating diagonalization that passes through is to described characteristic set N _SetHandle, obtain described separation matrix V and comprise:

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

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

Wherein, set $V^H{N}_{r}V=\left[\begin{array}{cc}{a}_r^{\&prime;}& b_r^{\&prime;}\\ c_r^{\&prime;}& d_r^{\&prime;}\end{array}\right],$ Diag () is by V for diagonal element ^HN _rThe matrix that the characteristic value of V is formed, Be V ^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;

(V N) carries out iteration optimization and handles, and obtains described separation matrix V to described target function C.

9, physical layer network code processing method according to claim 8 is characterized in that, described to described target function C (V N) carries out iteration optimization and handles, and obtains described separation matrix V and comprises:

According to target function C (V N) sets matrix T, and matrix T is:

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

Wherein, $a_r^{\&prime;}-d_r^{\&prime;}=(a_r-d_r)\cos 2\mathrm{\&alpha;}+(b_r-c_r)\sin 2\mathrm{\&alpha;}\cos \mathrm{\&beta;}+j(c_r-b_r)\sin 2\mathrm{\&alpha;}\sin \mathrm{\&beta;}=P^T{g}_r,$ P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TBe matrix Re (G ^HG) characteristic value characteristic of correspondence vector, gr=[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 vector of matrix, and according to described eigenvalue of maximum characteristic of correspondence vector sum formula P=[cos 2 α, sin 2 α cos β, sin 2 α sin β] ^TObtain corresponding α and β; If Δ V ^H, Δ V has the structure of hermitian, and $\mathrm{\&Delta;V}=\left[\begin{array}{cc}\cos \mathrm{\&alpha;}& -e^{\mathrm{j\&beta;}}\sin \mathrm{\&beta;}\\ e^{-\mathrm{j\&beta;}}\sin \mathrm{\&alpha;}& \cos \mathrm{\&alpha;}\end{array}\right],$ Carry out the updating value V that interative computation obtains separation matrix according to described α and β _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 then the updating value of Ci Shi separation matrix is described separation matrix V.

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

The described separation matrix V=I of initialization _n

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

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