CN102594524A - Orthogonal space-time block code transmission method based on an optimal relay linear weighting matrix - Google Patents

Abstract

The invention discloses an orthogonal space-time block code transmission method based on an optimal relay linear weighting matrix, which solves the problems of high error rate and poor transmission performance in the traditional method. The orthogonal space-time block code transmission method is realized by the following steps: (1) a communication system formed by a source node S, a relay node R and a destination node D is set; (2) at a first time slot, the source node S sends signal vectors x1 and x2, and the relay node R receives data yr1 and yr2; (3) the relay node R carries out singular value decomposition on a channel matrix H1 from the source node S to the relay node R and a channel matrix h2 from the relay node R to the destination node D; (4) the relay node R constructs an optimal linear weighting matrix W; (5) at a second time slot, the relay node R constructs and sends signal vectors xr1 and xr2 to the destination node D; and (6) the destination node D receives data yd1 and yd2 and constructs a judgment vector to decode. The orthogonal space-time block code transmission method disclosed by the invention has the advantages that: since the signal-to-noise ratio of received signals is increased, the system error rate is reduced, and the system transmission performance is improved.

Description

Orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying

Technical field

The invention belongs to communication technical field, relate to signal transmission in the relaying cooperation communication system, be based on the orthogonal space time block coding transmission method of the linear weighting matrix of optimum relaying specifically, can be used for many antennas relay system.

Background technology

In the wireless communication system, multiple-input and multiple-output MIMO antenna configurations can greatly improve reached at the capacity of the single output of traditional single input SISO system, and the branch collection can be provided, and multiplexingly waits gain.For example, in mimo system,, the spatial reuse gain can be obtained, and when adopting orthogonal space time block coding transmission method, then diversity gain can be obtained through adopting the vertical demixing time space transmission method.

But in practical application, on the one hand, because the volume and the power consumption constraints of communication terminal make mimo system to realize.On the other hand, because cooperation technology can obtain space diversity gain, and can expand the coverage area, so the auxiliary cooperation communication system of relaying receives much concern.Relaying subplan can be divided into two big types: regeneration scheme and non-regeneration scheme.In regeneration scheme, the signal that via node decoding is earlier received is encoded, and then is sent to destination node.And for non-regeneration scheme, its complexity is low, and the signal that via node only needs linear processing to receive is transmitted to destination node again.

For the auxiliary vertical demixing time space transmission method of non-regenerative relaying,, just can adopt a kind of simple amplification coefficient to carry out relaying if via node is only known the channel condition information CSI between source node and it self.Yet; If the CSI information between source node and the via node and between via node and the destination node is all known; Then can be through the rational linear weighted function matrix at design via node place, making systematic function has great raising when only adopting simple relaying amplification coefficient.

On the other hand, also obtained considerable research for the auxiliary orthogonal space time block coding transmission system of non-regenerative relaying shown in Figure 1.In system shown in Figure 1, comprise a source node S, a via node R and a destination node D.Wherein all nodes all are furnished with many antennas.Source node S is sent the space-time block coding data and is given via node R, and via node R receives the data from source node S, and carries out processing and amplifying, is transmitted to destination node D then.Wherein, during via node R processing and amplifying data, if via node R has no CSI information, what it adopted is the fixed gain coefficient.But when the relaying node R can obtain the CSI information between source node and the relaying, it can adopt the auxiliary simple weighted matrix based on gain coefficient of CSI to transmit.Research shows, through carrying out rational power control, adopts the auxiliary orthogonal space time block coding transmission method based on the gain coefficient weighting matrix of CSI can obtain with the identical performance of fixed relay gain method.But above these two kinds of methods all do not make full use of the linear process ability and the multi-antenna diversity gain of relaying, thus can cause the reduction of system's received signal to noise ratio and the decline of bit error rate performance, thus reduce the transmission performance of system.And; When the CSI information between source node and relaying and relaying and the destination node is all known; The optimum linearity weighting matrix at relaying place is unknown; Therefore the auxiliary orthogonal space time block coding transmission method of current non-regenerative relaying can not be optimum the information at processing relaying place, make the error rate of system performance very low, the system transmissions performance is limited.

Summary of the invention

The objective of the invention is to deficiency, propose a kind of orthogonal space time block coding transmission method, receive the signal to noise ratio of signal, thereby improve the bit error rate performance of system with raising based on the linear weighting matrix of optimum relaying to above-mentioned prior art.

The technical thought that realizes the object of the invention is; Through utilizing the CSI information between source node and relaying and relaying and the destination node; The optimum linearity weighting matrix of design retransmit, and improve existing orthogonal space time block coding transmission method, thus the diversity gain that effectively utilizes many antennas of relaying to provide; Make destination node can obtain maximum received signal to noise ratio, improve the error rate of system performance.Its concrete implementation procedure is following:

(1) set a source node S, a via node R and a destination node D making up the auxiliary orthogonal space time block coding transmission system of non-regenerative relaying, and are divided into two time slots with a transmission cycle of this system, and each time slot comprises two moment;

(2) source node S is sent signal in first time slot, and promptly in first moment, source node S is sent the primary signal vector x ₁Give via node R, in second moment, source node S is sent the signal vector x behind the space-time block coding ₂Give via node R, and x ₁And x ₂Satisfy following form:

$x_1=\left[\begin{array}{c}{m}_1\\ {\mathrm{<figure-callout\; id="2"\; label="m"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">m</figure-callout>}}_2\end{array}\right]$

$x_2=\left[\begin{array}{c}{-m}_2^{*}\\ {\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">m</figure-callout>}}_1^{*}\end{array}\right]$

Wherein, m ₁Be first modulation symbol at source node S place, m ₂Be second modulation symbol at source node S place, () ^*Represent conjugate operation;

(3) via node R receives data in first time slot, and promptly in first moment, first data that via node R receives are y _R1, in second moment, second data that via node R receives are y _R2

(4) via node R uses the training sequence estimation technique to obtain the channel matrix H of source node S to via node R ₁, and it is carried out singular value decomposition:

$H_1={\mathrm{<figure-callout\; id="1"\; label="U"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">U</figure-callout>}}_1\left[\begin{array}{c}{\widehat{\mathrm{\&Lambda;}}}_1\\ 0\end{array}\right]V_1^H={\mathrm{<figure-callout\; id="1"\; label="U"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">U</figure-callout>}}_1{\mathrm{\&Lambda;}}_1{V}_1^H$

Wherein, U ₁It is the channel matrix H that source node S arrives via node R ₁Left singular vector,

Be the diagonal matrix of (2 * 2) dimension, V ₁It is the channel matrix H that source node S arrives via node R ₁Right singular vector, ${\mathrm{\&Lambda;}}_1=\left[\begin{array}{c}{\widehat{\mathrm{\&Lambda;}}}_1\\ 0\end{array}\right]$ Be (N _r* 2) matrix of dimension, N _rBe the antenna number at via node R place, () ^HOperate for conjugate transpose;

(5) via node R obtains the channel matrix h of via node R to destination node D through feedback ₂, and it is carried out singular value decomposition:

${\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2=\left[\begin{array}{cc}{\mathrm{\&lambda;}}_{21}& 0\end{array}\right]V_2^H={\mathrm{\&Lambda;}}_2{V}_2^H$

Wherein, λ ₂₁Be the channel matrix h of via node R to destination node D ₂The non-zero singular value, V ₂Be the channel matrix h of via node R to destination node D ₂Right singular vector, Λ ₂=[λ ₂₁0] is N _rThe row vector of individual element;

(6) via node R is according to the channel matrix H of source node S to via node R ₁Left singular vector U ₁With the channel matrix h of via node R to destination node D ₂Right singular vector V ₂, structure makes the maximum optimum linearity weighting matrix W of received signal to noise ratio be:

$W=\sqrt{\frac{P_r}{E_S{\mathrm{\&lambda;}}_{11}^2+{\mathrm{\&sigma;}}_r^2}}{\left(V_2\right)}_1{\left(U_1\right)}_1^H$

Wherein, P _rBe the transmitted power of via node R, E _SBe the energy of source node S transmission symbol, λ ₁₁Be the channel matrix H of source node S to via node R ₁Singular value,

Be noise power, (V ₂) ₁Be the channel matrix h of via node R to destination node D ₂Right singular vector V ₂First column element, (U ₁) ₁Be the channel matrix H of source node S to via node R ₁Left singular vector U ₁First column element;

(7) in second time slot, via node R sends data, promptly first constantly, and optimum linearity weighting matrix W that via node R constructs step (6) and first reception data y in the step (3) _R1Multiply each other, obtain first transmission signal vector of relaying x _R1, and send to destination node D; Second constantly, second reception data y in the optimum linearity weighting matrix W that via node R constructs step (6) and the step (3) _R2Multiply each other, obtain second transmission signal vector x of relaying _R2, and send to destination node D;

(8) destination node D receives data in second time slot, and promptly in first moment, it is y that destination node D receives first data _D1, in second moment, it is y that destination node D receives second data _D2, and according to two data y that receive _D1And y _D2Structure judgement vector is to decipher.

The present invention has following advantage:

1) the present invention is through utilizing the channel condition information CSI between source node and the via node and between via node and the destination node; Construct the optimum linearity weighting matrix of retransmit; Make that receiving signal obtains maximum signal to noise ratio; And the orthogonal space time block coding transmission method based on the gain coefficient weighting matrix with traditional CSI is auxiliary is compared with the orthogonal space time block coding transmission method of fixed relay gain; The orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying of the present invention's design can obtain more high s/n ratio gain, has improved the error rate of system performance.

2) the present invention has made full use of the linear process ability at via node place through use the method for linear weighted function matrix at via node, has improved the detection performance that receives signal.

3) the present invention is through being dissolved into the multi-input multi-ouput channel state information in the optimum linearity weighting matrix, thereby made full use of the multi-antenna diversity gain, improved the reliability of input.

Description of drawings

Fig. 1 is the auxiliary orthogonal space time block coding transmission system sketch map of existing non-regenerative relaying;

Fig. 2 is that the present invention adopts the orthogonal space time block coding transfer process figure based on the linear weighting matrix of optimum relaying;

Fig. 3 is that the present invention sets the auxiliary orthogonal space time block coding transmission system sketch map of non-regenerative relaying;

Fig. 4 is the performance of BER comparison diagram that adopts the inventive method and traditional orthogonal space time block coding method;

Fig. 5 is the error sign ratio performance comparison diagram that adopts the inventive method and traditional orthogonal space time block coding method.

Embodiment

Followingly transmission method of the present invention is described in further detail with reference to accompanying drawing.

With reference to Fig. 2, the orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying that the present invention adopts comprises the steps:

Step 1: make up the auxiliary orthogonal space time block coding transmission system of non-regenerative relaying.

The orthogonal space time block coding transmission system that the non-regenerative relaying that the present invention makes up is auxiliary, as shown in Figure 3, this system is by a source node S, and a via node R and a destination node D constitute.Wherein, source node S has two antennas, and via node R has N _rRoot antenna, destination node D have an antenna.A transmission cycle of this communication system comprises two time slots, and each time slot comprises two moment.In addition, the present invention suppose any a pair of transmission/reception antennas between channel be flat fading channel, the channel fading coefficient remains unchanged in two time slots.And the known source node S of suppose relay node R of the present invention arrives the channel condition information CSI of destination node D to via node R and via node R.

Step 2: source node S is used power P _SSend two unlike signal vectors in two moment of first time slot respectively and give via node R.

In first moment, send the primary signal vector x by source node S ₁Give via node R, in second moment, by the signal vector x behind the source node S transmission space-time block coding ₂Give via node R, and x ₁And x ₂Satisfy following form:

$x_1=\left[\begin{array}{c}{m}_1\\ m_2\end{array}\right]---\left(1\right)$

$x_2=\left[\begin{array}{c}{-m}_2^{*}\\ {\mathrm{<figure-callout\; id="1"\; label="m"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">m</figure-callout>}}_1^{*}\end{array}\right]---\left(2\right)$

Wherein, m ₁Be first modulation symbol at source node S place, m ₂Be second modulation symbol at source node S place, () ^*Represent conjugate operation.

Step 3: via node R receives two different pieces of informations from source node S in two moment of first time slot respectively.

At first moment, first data y that via node R receives _R1For:

y _r1＝H ₁x ₁+n _r1 (3)

Wherein, H ₁Be the channel matrix of source node S to via node R, dimension is (N _r* 2), N wherein _rBe the antenna number at via node R place, n _R1Be first additive white Gaussian noise vector at via node R place, dimension is (N _r* 1), and n _R1Average be zero, variance matrix does

Wherein

Be the noise power at via node R place, I is a unit matrix;

At second moment, second data y that via node R receives _R2For:

y _r2＝H ₁x ₂+n _r2 (4)

Wherein, n _R2Be second the additive white Gaussian noise vector in via node R place, dimension is (N _r* 1), and n _R2Average be zero, variance matrix does

Step 4: via node R estimates the channel matrix H of source node S to via node R ₁, and to H ₁Carry out singular value decomposition.

Via node R estimates the channel matrix H of source node S to via node R ₁Can adopt several different methods of the prior art, the pilot frequency sequence estimation technique for example, the training sequence estimation technique, the blind estimation technique, the half-blindness estimation technique.This instance adopts the training sequence estimation technique to estimate the channel matrix H of source node S to via node R ₁Concrete implementation procedure is: source node S is sent known original training sequence and is given via node R; Decline training sequence after the process channel matrix effect that via node R receives; To the decline contrary and known original training sequence of training sequence of via node R multiplies each other then, obtains the channel matrix H of source node S to via node R ₁

Via node R is to the channel matrix H of source node S to via node R ₁Carry out singular value decomposition, carry out through following formula:

$H_1={\mathrm{<figure-callout\; id="1"\; label="U"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">U</figure-callout>}}_1\left[\begin{array}{c}{\widehat{\mathrm{\&Lambda;}}}_1\\ 0\end{array}\right]V_1^H={\mathrm{<figure-callout\; id="1"\; label="U"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">U</figure-callout>}}_1{\mathrm{\&Lambda;}}_1{V}_1^H---\left(5\right)$

Wherein, U ₁It is the channel matrix H that source node S arrives via node R ₁Left singular vector, Be the diagonal matrix of (2 * 2) dimension, V ₁It is the channel matrix H that source node S arrives via node R ₁Right singular vector, ${\mathrm{\&Lambda;}}_1=\left[\begin{array}{c}{\widehat{\mathrm{\&Lambda;}}}_1\\ 0\end{array}\right]$ Be (N _r* 2) matrix of dimension, () ^HOperate for conjugate transpose.

Step 5: via node R obtains the channel matrix h of via node R to destination node D ₂, and to h ₂Carry out singular value decomposition.

Via node R can obtain the channel matrix h of via node R to destination node D through several different methods in the prior art ₂, open loop estimation methods for example, closed-loop estimation method, feedback information method.This instance adopts the feedback information method, and concrete implementation procedure is: destination node D adopts the training sequence estimation technique to obtain the channel matrix h of via node R to destination node D earlier ₂, destination node D arrives via node R through based on feedback link the channel matrix h of destination node D then ₂Feed back to via node R.

Via node R is to the channel matrix h of relaying node R to destination node D ₂Carry out singular value decomposition, carry out through following formula:

${\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2=\left[\begin{array}{cc}{\mathrm{\&lambda;}}_{21}& 0\end{array}\right]V_2^H={\mathrm{\&Lambda;}}_2{V}_2^H---\left(6\right)$

Wherein, λ ₂₁Be the channel matrix h of via node R to destination node D ₂The non-zero singular value, V ₂Be the channel matrix h of via node R to destination node D ₂Right singular vector, Λ ₂=[λ ₂₁0] is N _rThe row vector of individual element.

Step 6: via node R makes up the optimum linearity weighting square that makes that received signal to noise ratio is maximum.

Via node R is according to the channel matrix H of source node S to via node R ₁Left singular vector U ₁With the channel matrix h of via node R to destination node D ₂Right singular vector V ₂, structure makes the maximum optimum linearity weighting matrix W of received signal to noise ratio be:

$W=\sqrt{\frac{P_r}{E_S{\mathrm{\&lambda;}}_{11}^2+{\mathrm{\&sigma;}}_r^2}}{\left(V_2\right)}_1{\left(U_1\right)}_1^H---\left(7\right)$

Wherein, P _rBe the transmitted power of via node R, E _SBe the energy of source node S transmission symbol, and E _S=P _S/ 2, λ ₁₁Be the channel matrix H of source node S to via node R ₁Singular value,

Be noise power, (V ₂) ₁Be the channel matrix h of via node R to destination node D ₂Right singular vector V ₂First column element, (U ₁) ₁Be the channel matrix H of source node S to via node R ₁Left singular vector U ₁First column element.

Step 7: in second time slot, via node R makes up two different pieces of informations two moment respectively and sends to destination node D.

First constantly, optimum linearity weighting matrix W that via node R constructs step 6 and first reception data y in the step 3 _R1Multiply each other, first sends data x to obtain relaying _R1, and send to destination node D, wherein:

x _r1＝Wy _r1＝WH ₁x ₁+Wn _r1 (8)

Second constantly, second reception data y in the optimum linearity weighting matrix W that via node R constructs step 6 and the step 3 _R2Multiply each other, obtain second on relaying and send data x _R2, and send to destination node D, wherein:

x _r2＝Wy _r2＝WH ₁x ₂+Wn _r2 (9)

Step 8: destination node D receives two different pieces of informations from via node R in two moment of second time slot respectively.

In first moment, destination node D receives first data y _D1For:

${\mathrm{<figure-callout\; id="1"\; label="y\; d"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">y</figure-callout>}}_d=h_2{\mathrm{<figure-callout\; id="1"\; label="x\; r"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">x</figure-callout>}}_r+{\mathrm{<figure-callout\; id="1"\; label="n\; d"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">n</figure-callout>}}_d={\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1{x}_1+{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{<figure-callout\; id="1"\; label="Wn\; r"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">Wn</figure-callout>}}_r+{\mathrm{<figure-callout\; id="1"\; label="n\; d"\; filenames="HDA0000151125440000011.png"\; state="\{\{state\}\}">n</figure-callout>}}_d={\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1{x}_1+{\hat{n}}_{d1}---\left(10\right)$

Wherein, n _D1Be first additive white Gaussian noise at destination node D place, and its average is zero, variance does

Be first equivalent noise at destination node D place, and its average is zero, variance does ${\widehat{\mathrm{\&sigma;}}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}}^2={\mathrm{\&sigma;}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}}^2+{\mathrm{\&sigma;}}_r^2{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WW}}^H{h}_2^H;$

In second moment, destination node D receives second data y _D2For:

${\mathrm{<figure-callout\; id="2"\; label="y\; d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">y</figure-callout>}}_d=h_2{\mathrm{<figure-callout\; id="2"\; label="x\; r"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">x</figure-callout>}}_r+{\mathrm{<figure-callout\; id="2"\; label="n\; d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">n</figure-callout>}}_d={\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1{x}_2+{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{<figure-callout\; id="2"\; label="Wn\; r"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">Wn</figure-callout>}}_r+{\mathrm{<figure-callout\; id="2"\; label="n\; d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">n</figure-callout>}}_d={\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1{x}_2+{\hat{n}}_{d2}---\left(11\right)$

Wherein, n _D2Be second additive white Gaussian noise at destination node D place, and its average is zero, variance does

Be second equivalent noise at destination node D place, and its average is zero, variance does ${\widehat{\mathrm{\&sigma;}}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}}^2={\mathrm{\&sigma;}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}}^2+{{\mathrm{\&sigma;}}_r}^2{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WW}}^H{h}_2^H.$

Step 9: destination node D is according to two data y that receive _D1And y _D2Make up the judgement vector.

Destination node D can make up the judgement vector through several different methods in the prior art, for example compels zero method, least mean-square error method, maximum ratio act of union.This instance adopts the maximum ratio act of union, and concrete realization is carried out according to the following steps:

(9a) destination node D first data y that will receive _D1With second data y _D2After, it is encapsulated as vector form

${\hat{y}}_d=\left[\begin{array}{c}{y}_{d1}\\ {\mathrm{<figure-callout\; id="2"\; label="y\; d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">y</figure-callout>}}_d^2\end{array}\right]\left[\begin{array}{cc}{\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_1& {\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_2\\ {\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_2^{*}& {-\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_1^{*}\end{array}\right]\left[\begin{array}{c}{x}_1\\ x_2\end{array}\right]+\left[\begin{array}{c}{\hat{n}}_{d1}\\ {\hat{n}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}2}^{*}\end{array}\right]=\mathrm{Hx}+{\hat{n}}_d---\left(12\right)$

Wherein, [h ₂WH ₁] _iBe vectorial h ₂WH ₁I element, i=1,2, $H=\left[\begin{array}{cc}{\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_1& {\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_2\\ {\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_2^{*}& {-\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_1^{*}\end{array}\right]$ Represent the compound channel matrix, $x=\left[\begin{array}{c}{m}_1\\ {\mathrm{<figure-callout\; id="2"\; label="m"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">m</figure-callout>}}_2\end{array}\right]$ Be the primary signal vector at source node S place, ${\hat{n}}_d=\left[\begin{array}{c}{\hat{n}}_{d1}\\ {\hat{n}}_{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">d</figure-callout>}2}^{*}\end{array}\right]$ Recombination noise vector for destination node D place;

(9b) destination node D carries out the conjugate transpose operation with the compound channel matrix H that obtains in the step (9a); And multiply each other with reception data vector

in the step (9a), construct judgement vector

and be:

${\tilde{y}}_d=H^H{\hat{y}}_d=\underset{i=1}{\overset{2}{\mathrm{\&Sigma;}}}{\left|{\left[{\mathrm{<figure-callout\; id="2"\; label="h"\; filenames="HDA0000151125440000041.png"\; state="\{\{state\}\}">h</figure-callout>}}_2{\mathrm{WH}}_1\right]}_i\right|}^{2}x+{\tilde{n}}_d---\left(13\right)$

Wherein, () ^HThe operation of expression conjugate transpose,

And its average is zero, and variance matrix does

Equivalent noise variance for destination node D place.

The judgement vector that step 10: destination node D utilizes step 9 to obtain is deciphered.

Destination node D can decipher through several different methods in the prior art, maximum-likelihood decoding method for example, and the Viterbi decoding method is based on the decoding method of minimum mean square error criterion.This instance adopts the maximum-likelihood decoding method; Specifically be embodied as: destination node D carries out Euclidean distance relatively with all signaling points in the planisphere at judgement vector

that obtains in the step (9b) and primary signal vector x place; And find out with the minimum signaling point of judgement vector Euclidean distance, obtain decode results

and be:

$\tilde{x}=\arg \underset{{\tilde{x}}_i\&Element;G}{\min }d({\tilde{y}}_d,{\tilde{x}}_i)---\left(14\right)$

Wherein,

is the some signaling points in the planisphere; G is the set of all signaling points in the signal constellation which; Some signaling points

Euclidean distance between the two in

expression judgement vector

and the planisphere, the minimum value of

expression all elements.

Effect of the present invention can further specify through following simulation result:

A. simulated conditions: set a relaying cooperative system, comprise a source node S, a via node node R and a destination node D.Source node S has two transmitting antennas, the number of antennas N at via node R place _rBe increased to 4 from 2, destination node D has a reception antenna.The modulation system that adopts is 4QAM.And the transmitted power of source node S is P _S=1, the transmitted power at via node R place is P _r=1, and the suppose relay node R is the same with the noise variance at destination node D place, promptly

Suppose that in addition channel is the Rayleigh flat fading channel, and the average of channel coefficients is zero, variance is 1.

B. emulation content:

That B1) adopts respectively that traditional orthogonal space time block coding transmission method and the present invention based on the gain coefficient weighting matrix propose carries out emulation to the average error bit rate BER of cooperating relay system with respect to the average transmission signal to noise ratio based on the orthogonal space time block coding transmission method of the linear weighting matrix of optimum relaying, and simulation result is as shown in Figure 4.

That B2) adopts respectively that traditional orthogonal space time block coding transmission method and the present invention based on the gain coefficient weighting matrix propose carries out emulation to the error sign ratio SER of cooperating relay system with respect to the average transmission signal to noise ratio based on the orthogonal space time block coding transmission method of the linear weighting matrix of optimum relaying, and simulation result is as shown in Figure 5.

C. simulation result:

As can beappreciated from fig. 4; The performance of BER curve that the orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying that adopts the present invention to propose is obtained is starkly lower than the performance of BER curve of traditional orthogonal space time block coding transmission method based on the gain coefficient weighting matrix; In via node R antenna number is 4, and bit error rate is 10 ^-3The time, the method that adopts the present invention's proposition is with respect to conventional method, and system can obtain the gain of 12.5dB, shows that the transmission method that adopts the present invention to propose can reduce error rate of system, improves the transmission performance of system.And; When using the method for the present invention's proposition; System's bit error rate can reduce along with the increase of via node R place antenna number, and when using conventional method, not variation when antenna number increases at via node R place of system's bit error rate; Show the diversity gain that the method that adopts the present invention to propose can more effectively utilize the many antennas in via node R place to provide, thus the reliability of raising input.

As can beappreciated from fig. 5; The error sign ratio performance curve that the orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying that adopts the present invention to propose is obtained is starkly lower than the error sign ratio performance curve of traditional orthogonal space time block coding transmission method based on the gain coefficient weighting matrix; In via node R antenna number is 4, and error sign ratio is 10 ^-3The time, the method that adopts the present invention's proposition is with respect to conventional method, and system can obtain the gain of 12.5dB, shows that the transmission method that adopts the present invention to propose can reduce system's error sign ratio, improves the transmission performance of system.And; When using the method for the present invention's proposition; System's error sign ratio can reduce along with the increase of via node R place antenna number, and when using conventional method, not variation when antenna number increases at via node R place of system's error sign ratio; Show the diversity gain that the method that adopts the present invention to propose can more effectively utilize the many antennas in via node R place to provide, thus the reliability of raising input.

In sum, the present invention compares with traditional orthogonal space time block coding transmission method based on the gain coefficient weighting matrix, has reduced the bit error rate and the error rate of system, thereby has improved the transmission performance of system.

Claims (3)

1. the orthogonal space time block coding transmission method based on the linear weighting matrix of optimum relaying comprises the steps:

(1) set a source node S, a via node R and a destination node D making up the auxiliary orthogonal space time block coding transmission system of non-regenerative relaying, and are divided into two time slots with a transmission cycle of this system, and each time slot comprises two moment;

(2) source node S is sent signal in first time slot, and promptly in first moment, source node S is sent the primary signal vector x ₁Give via node R, in second moment, source node S is sent the signal vector x behind the space-time block coding ₂Give via node R, and x ₁And x ₂Satisfy following form:

Wherein, m ₁Be first modulation symbol at source node S place, m ₂Be second modulation symbol at source node S place, () ^*Represent conjugate operation;

(3) via node R receives data in first time slot, and promptly in first moment, first data that via node R receives are y _R1, in second moment, second data that via node R receives are y _R2

(4) via node R uses the training sequence estimation technique to obtain the channel matrix H of source node S to via node R ₁, and it is carried out singular value decomposition:

Wherein, U ₁It is the channel matrix H that source node S arrives via node R ₁Left singular vector, Be the diagonal matrix of (2 * 2) dimension, V ₁It is the channel matrix H that source node S arrives via node R ₁Right singular vector,

Be (N _r* 2) matrix of dimension, N _rBe the antenna number at via node R place, () ^HOperate for conjugate transpose;

(5) via node R obtains the channel matrix h of via node R to destination node D through feedback ₂, and it is carried out singular value decomposition:

Wherein, λ ₂₁Be the channel matrix h of via node R to destination node D ₂The non-zero singular value, V ₂Be the channel matrix h of via node R to destination node D ₂Right singular vector, Λ ₂=[λ ₂₁0] is N _rThe row vector of individual element;

(6) via node R is according to the channel matrix H of source node S to via node R ₁Left singular vector U ₁With the channel matrix h of via node R to destination node D ₂Right singular vector V ₂, structure makes the maximum optimum linearity weighting matrix W of received signal to noise ratio be:

Wherein, P _rBe the transmitted power of via node R, E _SBe the energy of source node S transmission symbol, λ ₁₁Be the channel matrix H of source node S to via node R ₁Singular value,

Be noise power, (V ₂) ₁Be the channel matrix h of via node R to destination node D ₂Right singular vector V ₂First column element, (U ₁) ₁Be the channel matrix H of source node S to via node R ₁Left singular vector U ₁First column element;

(7) in second time slot, via node R sends data, promptly first constantly, and optimum linearity weighting matrix W that via node R constructs step (6) and first reception data y in the step (3) _R1Multiply each other, obtain first transmission signal vector of relaying x _R1, and send to destination node D; Second constantly, second reception data y in the optimum linearity weighting matrix W that via node R constructs step (6) and the step (3) _R2Multiply each other, obtain second transmission signal vector x of relaying _R2, and send to destination node D;

(8) destination node D receives data in second time slot, and promptly in first moment, it is y that destination node D receives first data _D1, in second moment, it is y that destination node D receives second data _D2, and according to two data y that receive _D1And y _D2Structure judgement vector is to decipher.

2. method according to claim 1, wherein the described destination node D of step (8) is according to two data y that receive _D1And y _D2Structure judgement vector comprises the steps:

(8a) destination node D first data y that will receive _D1With second data y _D2Be encapsulated as vector form

Obtain:

Wherein, [h ₂WH ₁] _i, i=1,2 is vectorial h ₂WH ₁I element,

Be first equivalent noise at destination node D place,

Be second equivalent noise at destination node D place,

Represent the compound channel matrix, Be the primary signal vector at source node S place,

Recombination noise vector for destination node D place;

(8b) destination node D structure judgement vector is:

Wherein, () ^HFor the conjugate transpose operation,

3. method according to claim 1; Wherein the described destination node D of step (8) deciphers according to the judgement vector; Be that destination node D carries out Euclidean distance relatively with all signaling points in the planisphere at judgement vector

that obtains in the step (8b) and primary signal vector x place; And find out with the minimum signaling point of judgement vector

Euclidean distance, obtain decode results

and be:

Wherein, Some signaling points in

expression planisphere; The set of all signaling points in the G expression signal planisphere; Some signaling points

Euclidean distance between the two in

expression judgement vector and the planisphere,

(minimum value of expression all elements.

Images