CN102932041B - Method for encoding and decoding asynchronous space-time code for collaborative multi-point transmission - Google Patents

Abstract

The invention discloses a method for encoding and decoding an asynchronous space-time code for collaborative multi-point transmission, to solve the problem that the collaborative communication can not be carried out due to time asynchronization and frequency offset during collaborative multi-point joint processing. The method comprises the following specific steps that: (1) user equipment estimates the channel parameter and feeds back the channel parameter to remote wireless equipment; (2) different remote wireless equipment constructs delay convolutional encoding matrixes; (3) the user equipment estimates the overall equivalent channel matrix of the remote wireless equipment; (4) the user equipment constructs the frequency offset matrix; (5) an eNodeB evolutional base station transmits the symbol sequence; (6) the remote wireless equipment carries out space-time coding on the information sequence and sends the information sequence; (7) the user equipment carries out frequency compensation on the received symbol sequence; and (8) the user equipment judges the feedback decoding by using the minimum mean square error and decodes. Due to the adoption of the method, the full-mark set gain can be obtained without carrying out accurate time and frequency synchronization, and the decoding complexity is reduced.

Description

Asynchronous empty time-code decoding method in cooperative multipoint transmission

Technical field

The invention belongs to communication technical field, relate to asynchronous empty time-code technology, particularly a kind of asynchronous empty time-code decoding method for cooperative multicast system, can be used for the distributed collaborative multicast system of future wireless system.

Background technology

In multi cell cellular system, pass through to adopt MIMO technology, can improve the spectrum efficiency of communication system, but the existence of disturbing due to common road, make the throughput of edge cell can not get effective raising, in order to address this problem, coordinate multipoint CoMP transmission technology is proposed in MIMO technical foundation.In CoMP, the far-end wireless device of multiple communities cooperates mutually, can communicate with the user of edge cell simultaneously, not only can improve system reliability, can also further improve the throughput of edge cell and the throughput of total system.CoMP transmission technology comprises cooperative scheduling CS pattern and Combined Treatment JP pattern, wherein CoMP-JP pattern can be by multiple far-end wireless device simultaneously to user device transmissions data, such as far-end wireless device 1 and far-end wireless device 2 sends data to the subscriber equipment 1 in two cell boarders simultaneously, in CoMP-JP, all far-end wireless device are controlled by same evolved base station eNodeB, all far-end wireless device are eliminated inter-user interference after information consolidation is processed, send to again subscriber equipment simultaneously, interference signal is become to useful signal to be used, thereby can effectively utilize the interference of minizone.The gain of CoMP-JP is from two aspects: one, and participating in the signal that the community of cooperation sends is all useful signal, total interference level that terminal is subject to has reduced; Its two, the cell signal that participates in cooperation superposes mutually, has improved the power level of the signal that terminal receives, in addition, between the antenna of different districts, general distance is larger, much larger than half-wavelength, Combined Treatment also likely obtains diversity gain, improves service quality and the throughput of Cell Edge User.

Coordinate multipoint Combined Treatment CoMP-JP pattern can be applied to single or multiple user equipment (UE)s under the resource situation of given time domain and frequency domain, under the scene of many far-end wireless device and multi-user installation, time between different far-end wireless device and subscriber equipment and Frequency Synchronization cannot solve by conventional method simultaneously, research shows, along with the increase of UE and RRE number, the possibility that system completes precise time and Frequency Synchronization reduces, and even possibility goes to zero.Existing process when empty and encoding and decoding technique cannot be applied to time and all scenes of non-precise synchronization of frequency, therefore need to study processing and encoding and decoding technique when time and the non-precise synchronization of frequency are had to certain tolerance empty for coordinate multipoint Combined Treatment CoMP-JP pattern.

Summary of the invention

The object of the invention is to overcome the deficiency of above-mentioned prior art, asynchronous empty time-code decoding method in a kind of cooperative multipoint transmission is proposed, can effectively obtain full diversity gain, improve service quality and the throughput of Cell Edge User, improve the reliability of cooperation communication system.

For achieving the above object, asynchronous empty time-code decoding method in cooperative multipoint transmission of the present invention, concrete steps are as follows:

(1) system initialization: different far-end wireless device adopt least mean-square error channel estimation methods, respectively channel parameter information, time delay information and the frequency offset information between estimating user equipment and multiple different far-end wireless device; Information obtained above is fed back to corresponding far-end wireless device by subscriber equipment;

(2) structure time delay convolutional encoding matrix:

2a) far-end wireless device utilizes alternative manner to calculate translation full rank polynomial sequence: { P ₁(x), P ₂(x) ... P _r(x) }, wherein, P _r(x) be the translation full rank multinomial at r far-end wireless device place, the number that R is far-end wireless device, meets R > 1, r=1 ... R;

2b) to above-mentioned { P ₁(x), P ₂(x) ... P _r(x) } translation full rank polynomial sequence is normalized, and obtains the translation full rank polynomial sequence after normalization:

$\{P_1\left(x\right)/\sqrt{R},P_2\left(x\right)/\sqrt{R},\·\·\·\·\·\·,P_R\left(x\right)/\sqrt{R}\},$

Wherein, it is the normalization translation full rank multinomial at r far-end wireless device place;

2c) to the translation full rank polynomial sequence after normalization in each multinomial write corresponding x power coefficient as one dimension code word matrix form according to high order power to the order of low order power, wherein, the coefficient null representation of default x power, obtains the one dimension code word matrix at r far-end wireless device place:

${\stackrel{\‾}{t}}^{\left(r\right)}=[{{\stackrel{\‾}{t}}_U}^{\left(r\right)},{{\stackrel{\‾}{t}}_{U-1}}^{\left(r\right)},\·\·\·{{\stackrel{\‾}{t}}_1}^{\left(r\right)}],$

Wherein, U is the length of one dimension code word matrix, meets for multinomial middle x power is the corresponding coefficient of i-1, i=1 ... U;

2d) according to the one dimension code word matrix at r far-end wireless device place obtain the convolutional encoding matrix at r far-end wireless device place

Wherein, convolutional encoding matrix dimension matrix, N is the number that eNodeB evolved base station sends symbol sebolic addressing;

2e) to convolutional encoding matrix use the method for zero padding, obtain the time delay convolutional encoding matrix of r far-end wireless device

${\hat{T}}^{\left(r\right)}=\left[\begin{array}{ccc}{0}_{N\×{\mathrm{\τ}}_r}& {\stackrel{\‾}{T}}^{\left(r\right)}& 0_{N\×({\mathrm{\τ}}_{\max }-{\mathrm{\τ}}_r)}\end{array}\right],$

Wherein, time delay convolutional encoding matrix dimension matrix, for N × τ _rthe full null matrix of dimension, for N × (τ _max-τ _r) dimension full null matrix, τ _rbe the time delay between r far-end wireless device and subscriber equipment, τ _max=max{ τ ₁... τ _r;

(3) subscriber equipment is estimated far-end wireless device entirety equivalent channel matrix

(4) subscriber equipment is constructed the frequency shift (FS) matrix of different far-end wireless device to subscriber equipment:

Wherein, frequency shift (FS) matrix e _rfor M × M ties up matrix, T _sfor mark space, M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max), f _rbe the frequency shift (FS) between r far-end wireless device and subscriber equipment, j is imaginary number unit, and k gets positive integer arbitrarily, and π is constant 3.14, and e is constant 2.71828183;

(5) eNodeB evolved base station sends symbol sebolic addressing S=[s to all far-end wireless device simultaneously ₀, s ₁... .., s _n-1], wherein, s _βrepresent the symbol that different time-gap sends, meet β=0 ..., N-1;

(6) different far-end wireless device are all to the symbol sebolic addressing S=[s receiving ₀, s ₁... .., s _n-1] carry out Space Time Coding, the Space Time Coding sequence that each far-end wireless device place sends is:

$Q_r={\left[{\hat{T}}^{\left(r\right)}\right]}^T{S}^T,$

Wherein, [] ^trepresent transposition computing, be r far-end wireless device time delay convolutional encoding matrix;

(7) subscriber equipment receives Space Time Coding sequence Q _rand utilize frequency shift (FS) matrix e _rit is carried out to frequency compensation, obtain the symbol sebolic addressing y after subscriber equipment frequency compensation, wherein, r=1 ... R;

(8) subscriber equipment to frequency compensation after symbol sebolic addressing y, utilize least mean-square error decision-feedback coding/decoding method to decode.

The present invention compared with prior art has the following advantages:

1. in cooperative multicast system of the present invention, because far-end wireless device is carried out Space Time Coding by structure time delay convolutional encoding matrix to the symbol sebolic addressing receiving, each far-end wireless device can be operated under asynchronous scene, not need precise time synchronous; Subscriber equipment carries out frequency compensation by structure frequency shift (FS) matrix to the symbol sebolic addressing receiving, and system is reduced for frequency shift (FS) susceptibility.

2. in cooperative multicast system of the present invention, because different far-end wireless device after carrying out Space Time Coding and frequency compensation can be regarded time and Frequency Synchronization as to the symbol sebolic addressing of subscriber equipment, subscriber equipment can merge multipath reception signal, thereby system obtains full diversity gain.

3. the complexity of the least mean-square error decision-feedback coding/decoding method in cooperative multicast system of the present invention is with linear growth, and complexity is lower.

4. the present invention only need to construct the convolutional encoding matrix at different far-end wireless device place in advance, can realize independently Space Time Coding of different far-end wireless device place, and implementation complexity is low.

Brief description of the drawings

Fig. 1 is the scene schematic diagram of the applicable coordinate multipoint joint transmission communication of the present invention;

Fig. 2 is FB(flow block) of the present invention;

Fig. 3 is the sub-process figure of translation full rank polynomial sequence of the present invention;

Fig. 4 is the sub-process figure of least mean-square error decision-feedback decoding of the present invention;

Fig. 5 be the present invention under two far-end wireless device scenes the error rate about the analogous diagram of signal to noise ratio;

Fig. 6 be the present invention under three far-end wireless device scenes the error rate about the analogous diagram of signal to noise ratio;

Fig. 7 be the present invention under three far-end wireless device scenes the error rate about the analogous diagram of frequency deviation variance.

Embodiment

Below in conjunction with accompanying drawing, embodiment of the present invention is described in further detail.

With reference to Fig. 1, coordinate multipoint joint transmission communication scenes comprises an eNodeB evolved base station, and R far-end wireless device and 1 subscriber equipment, meet R > 1.ENodeB evolved base station is provided with an antenna, and far-end wireless device is all provided with an antenna, and subscriber equipment is provided with an antenna.ENodeB evolved base station is all connected with optical fiber with far-end wireless device, and between different far-end wireless device and eNodeB evolved base station, regard Time And Frequency as and synchronize, between far-end wireless device and subscriber equipment, be flat fading wireless channel.ENodeB evolved base station sends identical information symbol sequence by optical fiber to each far-end wireless device; Far-end wireless device will receive to such an extent that information symbol sequence carries out Space Time Coding, then send to subscriber equipment through flat fading wireless channel separately; Subscriber equipment receives the information sequence from different far-end wireless device, and utilizes least mean-square error decision-feedback to decode, and demodulation recovers the information that eNodeB evolved base station sends.

The present invention complete cooperative multicast system asynchronous empty time-code encoding and decoding process as shown in Figure 2, the step of its realization is as follows:

Step 1, system initialization:

1a) different districts far-end wireless device transmitted signal sequence, subscriber equipment adopts paper Mehrzad Biguesh etc., " Training-based MIMO channel estimation:a study of estimator tradeoffs and optimaltraining signals " IEEE Trans.Signal Processing, vol.54, no.3, Mar.2006. the least mean-square error channel estimation methods in, estimate the channel parameter information of different districts far-end wireless device to subscriber equipment, h _rbe the channel parameter information between r far-end wireless device and subscriber equipment, wherein the value of r is r=1,2 ..., R;

1b) different districts far-end wireless device transmitted signal sequence, subscriber equipment adopts paper Mehrzad Biguesh etc., " Training-based MIMO channel estimation:a study of estimator tradeoffs and optimaltraining signals " IEEE Trans.Signal Processing, vol.54, no.3, Mar.2006. the least mean-square error channel estimation methods in, estimate the frequency shift (FS) of different districts far-end wireless device to subscriber equipment, f _rit is the frequency shift (FS) between r far-end wireless device and subscriber equipment;

1c) different districts far-end wireless device transmitted signal sequence, subscriber equipment adopts paper Mehrzad Biguesh etc., " Training-based MIMO channel estimation:a study of estimator tradeoffs and optimaltraining signals " IEEE Trans.Signal Processing, vol.54, no.3, Mar.2006. the least mean-square error channel estimation methods in, estimate the time delay of different districts far-end wireless device to subscriber equipment, τ _rit is the time delay between r far-end wireless device and subscriber equipment;

1d) subscriber equipment feeds back to corresponding far-end wireless device by different districts obtained above far-end wireless device to channel parameter information, frequency offset information and the time delay information of subscriber equipment.

Step 2, structure far-end wireless device place time delay convolutional encoding matrix:

2a) far-end wireless device utilizes alternative manner to calculate translation full rank polynomial sequence { P ₁(x), P ₂(x) ... P _r(x) }, wherein, P _r(x) be the translation full rank multinomial at r far-end wireless device place, the number that R is far-end wireless device, meets R > 1, r=1 ... R;

With reference to Fig. 3, being implemented as follows of this step:

2a1) iterations n is initialized as 1, and translation full rank polynomial sequence is initialized as { P ₁(x)=1};

2a2) make iterations n from increasing 1, the translation full rank polynomial sequence { P while judging iterations n-1 ₁(x), P ₂(x) ... P _n-1(x) P } ₁(x), P ₂(x) ... P _n-1(x) greatest common divisor between, if greatest common divisor GCD is 1, forwards step 2a3 to); If greatest common divisor GCD is u (x), wherein u (x) is not equal to 1, forwards step 2a4 to);

2a3) select two multinomial q ₂(x) and meet q ₂(x) aliquant wherein multinomial q ₂(x) be any multinomial that the highest power number is 1, multinomial that the highest power number is any multinomial of n-1, according to { P ₁(x), P ₂(x) ... P _n-1(x) }, q ₂(x) and translation full rank polynomial sequence while obtaining iterations n $\{P_1\left(x\right),P_2\left(x\right),\·\·\·P_{n-1}\left(x\right),P_n\}=\{q_2\left(x\right)P_1\left(x\right),q_2\left(x\right)P_2\left(x\right),\·\·\·q_2\left(x\right)P_n\left(x\right),{\hat{q}}_n\left(x\right)\};$

2a4) select two multinomial q ₂(x) and meet q ₂(x) aliquant wherein multinomial q ₂(x) be any multinomial that the highest power number is 1, multinomial that the highest power number is any multinomial of n-1, according to { P ₁(x), P ₁(x) ... P _n-1(x) }, q ₂(x) and translation full rank polynomial sequence while obtaining iterations n $\{P_1\left(x\right),P_2\left(x\right),\·\·\·P_{n-1}\left(x\right),P_n\}=\{P_1\left(x\right),P_2\left(x\right),\·\·\·P_n\left(x\right),{\hat{q}}_n\left(x\right)\};$

2a5) judge whether iterations n equals R, if iterations n=R obtains translation full rank polynomial sequence { P corresponding to all far-end wireless device ₁(x), P ₂(x) ... P _r(x) }; If iterations n < is R, carry out above-mentioned steps 2a2);

Translation full rank polynomial sequence { P corresponding to all far-end wireless device 2b) above-mentioned steps being obtained ₁(x), P ₂(x) ... P _r(x) } obtain according to the following formula normalized translation full rank polynomial sequence:

$\{P_1\left(x\right)/\sqrt{R},P_2\left(x\right)/\sqrt{R},\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;,P_R\left(x\right)/\sqrt{R}\}$

Wherein, the normalization translation full rank multinomial at r far-end wireless device place;

2c) to each multinomial in normalized translation full rank polynomial sequence obtained above write corresponding x power coefficient as one dimension code word matrix form according to high order power to the order of low order power, the wherein coefficient null representation of default x power, obtains the one dimension code word matrix at r far-end wireless device place:

${\stackrel{\&OverBar;}{t}}^{\left(r\right)}=[{{\stackrel{\&OverBar;}{t}}_U}^{\left(r\right)},{{\stackrel{\&OverBar;}{t}}_{U-1}}^{\left(r\right)},\&CenterDot;\&CenterDot;\&CenterDot;{{\stackrel{\&OverBar;}{t}}_1}^{\left(r\right)}]$

Wherein, U is the length of one dimension code word matrix, meets U=R-1, for multinomial middle x power is the corresponding coefficient of i-1, for default x power, equal zero, wherein i=1 ... U, for example multinomial x ⁶+ x ⁴+ x ³the one dimension code word matrix that+x+1 is corresponding is [1,0,1,1,0,1,1];

2d) by the one dimension code word matrix at different far-end wireless device obtained above place according to following make, obtain the convolutional encoding matrix at different far-end wireless device place, the convolutional encoding matrix at r far-end wireless device place is:

Wherein, dimension matrix, N is the number that eNodeB evolved base station sends symbol sebolic addressing, U is the length of one dimension code word matrix;

Characteristic 2e) postponing to subscriber equipment life period according to different far-end wireless device, to the convolutional encoding matrix of above-mentioned r far-end wireless device use the method for zero padding, protect interval to protect symbol sebolic addressing by interpolation, the maximum time of wherein protecting interval to equal between different far-end wireless device and subscriber equipment postpones τ _max=max{ τ ₁... ... τ _r, r far-end wireless device time delay convolutional encoding matrix expression is as follows:

${\hat{T}}^{\left(r\right)}=\left[\begin{array}{ccc}{0}_{N\&times;{\mathrm{\&tau;}}_r}& {\stackrel{\&OverBar;}{T}}^{\left(r\right)}& 0_{N\&times;({\mathrm{\&tau;}}_{\max }-{\mathrm{\&tau;}}_r)}\end{array}\right],$

Wherein, time delay convolutional encoding matrix dimension matrix, for N × τ _rthe full null matrix of dimension, for N × (τ _max-τ _r) dimension full null matrix, τ _rit is the time delay between r far-end wireless device and subscriber equipment.

Step 3, subscriber equipment is estimated far-end wireless device entirety equivalent channel matrix:

3a) eNodeB evolved base station, before sending symbol sebolic addressing, first sends the known training sequence A=[A of subscriber equipment to all far-end wireless device ₀, A ₁... .., A _n-1], wherein A _αrepresent the symbol that different time-gap sends, α=0 ..., N-1;

3b) different far-end wireless device is utilized time delay convolutional encoding matrix obtained above all the training sequence A receiving is carried out to Space Time Coding, r far-end wireless device be the Space Time Coding training sequence W after Space Time Coding to training sequence _r:

$W_r={\left[{\hat{T}}^{\left(r\right)}\right]}^t{A}^T$

Wherein, Space Time Coding training sequence W _rdimension be M × 1 dimension, [] ^trepresent transposition computing;

3c) different far-end wireless device is by Space Time Coding training sequence W separately _rsend to subscriber equipment, subscriber equipment receives training symbol sequence expression formula as follows:

$\tilde{y}={\left[\begin{array}{cccc}{h}_1{W_1}^T& h_2{W_2}^T& \&CenterDot;\&CenterDot;\&CenterDot;& h_R{W_R}^T\end{array}\right]}^T+I$

$={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T{A}^T+I$

Wherein, subscriber equipment receives training symbol sequence dimension be MR × 1 dimension, h _rbe the channel parameter information between r far-end wireless device and subscriber equipment, I is the noise matrix of MR × 1 dimension, and wherein all to obey average be 0 to every one dimension, and variance is multiple Gaussian Profile, M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max), [] ^trepresent transposition computing;

3d) subscriber equipment utilizes known training sequence A and least mean-square error channel estimation methods to receive training symbol sequence to subscriber equipment carry out channel estimating, estimate far-end wireless device entirety equivalent channel matrix $\hat{H}={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T.$

Step 4, subscriber equipment utilizes step 1b) estimate that the different far-end wireless device that obtain arrive the frequency shift (FS) f of subscriber equipment _r, construct the frequency shift (FS) matrix of different far-end wireless device to subscriber equipment, the far-end wireless device frequency shift (FS) matrix e of r, subscriber equipment place _r:

Wherein, frequency shift (FS) matrix e _rfor M × M ties up matrix, T _sfor information symbol interval, M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max), j is imaginary number unit, and k gets positive integer arbitrarily, and π is constant 3.14, and e is constant 2.71828183.

Step 5, eNodeB evolved base station sends symbol sebolic addressing S=[s to all far-end wireless device simultaneously ₀, s ₁... .., s _n-1], wherein s _βrepresent the symbol that different time-gap sends, wherein β=0 ..., N-1, N is the number that eNodeB evolved base station sends symbol sebolic addressing.

Step 6, different far-end wireless device are utilized the time delay convolutional encoding matrix of r the far-end wireless device that above-mentioned steps obtains to the symbol sebolic addressing S=[s receiving ₀, s ₁... .., s _n-1] carry out respectively Space Time Coding, r far-end wireless device Space Time Coding sequence after Space Time Coding:

$Q_T={\left[{\hat{T}}^{\left(r\right)}\right]}^T{S}^T$

Wherein, Q _rbe the Space Time Coding sequence at r far-end wireless device place, dimension is M × 1 dimension, and M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max), [] ^trepresent transposition computing.

Step 7, the go forward side by side line frequency compensation of subscriber equipment receiving symbol sequence:

7a) different far-end wireless device is by the information sequence Q after Space Time Coding _rsend to subscriber equipment, the expression formula of subscriber equipment place receiving symbol sequence is as follows:

$\hat{y}={\left[\begin{array}{cccc}{h}_1{Q_1}^T& h_2{Q_2}^T& \&CenterDot;\&CenterDot;\&CenterDot;& h_R{Q_R}^T\end{array}\right]}^T+n$

$={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T{S}^T+n=\hat{H}{S}^T+n$

Wherein, h _rbe the channel parameter information between r far-end wireless device and subscriber equipment, Q _rbe the Space Time Coding sequence at r far-end wireless device place, $\hat{H}={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T$ For far-end wireless device entirety equivalent channel matrix, n is the noise matrix of MR × 1 dimension, and wherein all to obey average be 0 to every one dimension, and variance is multiple Gaussian Profile, [] ^trepresent transposition computing, M is different far-end wireless device time delay convolutional encoding matrixes columns, i.e. M=(N+U-1+ τ _max);

7b) subscriber equipment utilizes r far-end wireless device frequency shift (FS) matrix e to the information sequence from r far-end wireless device place receiving _rcarry out frequency compensation, the symbol sebolic addressing y expression formula after subscriber equipment frequency compensation is as follows:

$y=\left[\begin{array}{cccc}{e}_1& e_2& \&CenterDot;\&CenterDot;\&CenterDot;& e_R\end{array}\right]\hat{H}{S}^T+\left[\begin{array}{cccc}{e}_1& e_2& \&CenterDot;\&CenterDot;\&CenterDot;& e_R\end{array}\right]n=H{S}^T+\hat{n}$

Wherein, the dimension of y is M × 1 dimension, $H=\left[\begin{array}{cccc}{e}_1& e_2& \&CenterDot;\&CenterDot;\&CenterDot;& e_R\end{array}\right]\hat{H}$ For the equivalent channel matrix after frequency compensation, for the noise matrix of M × 1 dimension, wherein all to obey average be 0 to every one dimension, and variance is multiple Gaussian Profile, M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max).

Step 8, subscriber equipment adopts paper H.Wang to the symbol sebolic addressing y after frequency compensation, X.-G.Xia, and Q.Yin, " Computationally efficient equalization for asynchronous cooperativecommunications with multiple frequency offsets, " IEEE Trans.Wireless Commun., vol.8, no.2, pp.648 – 655, the least mean-square error decision-feedback in Feb.2009. is decoded:

With reference to Fig. 4, being implemented as follows of this step:

8a) according to above-mentioned equivalent channel matrix H after frequency compensation according to formula construction companion matrix R below, companion matrix R matrix is for generating rear end feedback filtering matrix and the front end feedback filtering matrix of decode procedure:

$R=H^{H}H+\frac{{\mathrm{\&sigma;}}_n^2}{{\mathrm{\&sigma;}}_s^2}{I}_N$

Wherein, the dimension of R is N × N, [] ^hrepresent conjugate transpose computing, H ^hrepresent the conjugate transpose of H, for the variance of each element in noise matrix n, for sending symbol sebolic addressing S=[s ₀, s ₁... .., s _n-1] power, I _nfor the unit matrix of N × N dimension;

8b) above-mentioned companion matrix R is carried out to Cholesky decomposition:

R＝L?D?L ^H，

Wherein, L is that diagonal entry is 1 lower triangular matrix, l ^hrepresent the conjugate transpose of L, D is the diagonal matrix of N × N dimension;

8c) utilizing above-mentioned diagonal entry is 1 lower triangular matrix L and companion matrix R, constructs respectively rear end feedback filtering matrix B and front end feedback filtering matrix F:

F＝LR ^-1H ^H，

Wherein, the dimension of B is N × N dimension, I _nfor the unit matrix of N × N dimension, b _gbe the row vector of 1 × N dimension, g=0 ..., N-1, the dimension of F is N × N dimension, H ^hrepresent the conjugate transpose of H, [] ^-1represent to get inverse operation, R ^-1expression companion matrix R's is contrary;

The symbol sebolic addressing y that 8d) utilizes above-mentioned front end feedback filtering matrix F to carry out after frequency compensation subscriber equipment carries out forward direction filtering, obtains the filtered vector Z of forward direction:

Z＝Fy＝[z ₀,z ₁……z _N-1] ^T

Wherein, the dimension of Z is N × 1 dimension N × N, z _γrepresent forward direction filtered vector Z=[z ₀, z ₁z _n-1] ^tin γ element, γ=0 ..., N-1, [] ^trepresent transposition computing;

8e) according to above-mentioned rear end feedback filtering matrix B and the filtered vector Z of forward direction, realize the decoding to information sequence according to formula below:

${\hat{s}}_j=\left\{\begin{array}{cc}\mathrm{\&theta;}\left(z_0\right)& j=0\\ \mathrm{\&theta;}(z_j-{b^{*}}_j{\hat{S}}_{j-1})& 1\&le;j\&le;N-1\end{array}\right.$

Wherein, θ (z ₀) represent symbol z ₀in planisphere, find and symbol z ₀the constellation point of Euclidean distance minimum represent symbol in planisphere, find and symbol the constellation point of Euclidean distance minimum z _jrepresent forward direction filtered vector Z=[z ₀, z ₁z _n-1] ^tin j element, represent j × 1 dimensional decoding symbolic vector, b ^* _jfor the capable b of j+1 in the feedback filtering matrix B of rear end _jfront j+1 row, wherein, b _jcan be expressed as b _j=[b ^* _j, 0 _{1 × (N-j)}], b _jin 0 _{1 × (N-j)}be 1 × (N-j) complete zero row vector of dimension, b ^* _jit is the row vector of 1 × j dimension.

Effect of the present invention can further illustrate by emulation:

(1) simulated conditions

Modulation system adopts QPSK, the channel independent same distribution between far-end wireless device and subscriber equipment, and obeying average is 0, the quasistatic Rayleigh flat fading that variance is 1.Normalization frequency deviation independent same distribution in Fig. 5 and Fig. 6 between different far-end wireless device and subscriber equipment, all obeying average is 0, variance is normal distribution; In Fig. 7 in the situation that signal to noise ratio is 25dB, the normalization frequency deviation independent same distribution between different far-end wireless device and subscriber equipment, all obeying average is 0, variance is normal distribution, wherein span is (0,0.25).Delay between different far-end wireless device and subscriber equipment is at [0, τ _max] in obey be uniformly distributed, maximum delay τ _maxand the length of zero padding is all 4, the length of information symbol frame is 20.

(2) emulation content and result

Emulation 1, the in the situation that of two far-end wireless device and a subscriber equipment, adopt respectively the decoding of decoding forwarding-least mean-square error, the decoding of decoding forwarding-least mean-square error decision-feedback, decoding forwarding-Maximum likelihood sequence detection, asynchronous empty time-code-least mean-square error of the present invention decoding, asynchronous empty time-code-least mean-square error decision-feedback decoding of the present invention, 6 kinds of patterns of asynchronous empty time-code-Maximum likelihood sequence detection of the present invention, average error rate is carried out to emulation with respect to average signal-to-noise ratio, and result as shown in Figure 5;

Emulation 2, the in the situation that of three far-end wireless device and a subscriber equipment, adopt respectively the decoding of decoding forwarding-least mean-square error, the decoding of decoding forwarding-least mean-square error decision-feedback, decoding forwarding-Maximum likelihood sequence detection, the decoding of asynchronous empty time-code-least mean-square error, asynchronous empty time-code-least mean-square error decision-feedback decoding of the present invention, 6 kinds of patterns of asynchronous empty time-code-Maximum likelihood sequence detection of the present invention, average error rate is carried out to emulation with respect to average signal-to-noise ratio, and result as shown in Figure 6.

The simulation result of Fig. 5 and Fig. 6 shows: in the time that signal to noise ratio is larger, the ber curve of asynchronous empty time-code-least mean-square error decision-feedback decoding of the present invention is starkly lower than the ber curve of decoding forwarding-least mean-square error decision-feedback decoding, and the error rate of the asynchronous empty time-code-least mean-square error decision-feedback coding/decoding method of the present invention is lower; No matter at asynchronous empty time-code or in the situation that decoding forwards, adopt the decoding of least mean-square error decision-feedback and adopt the slope of curve of Maximum likelihood sequence detection along with signal to noise ratio increase convergence is identical, the decoding of least mean-square error decision-feedback can obtain the diversity gain identical with Maximum likelihood sequence detection.

Emulation 3, the in the situation that of three far-end wireless device and a subscriber equipment, adopt respectively the decoding of decoding forwarding-least mean-square error, the decoding of decoding forwarding-least mean-square error decision-feedback, decoding forwarding-Maximum likelihood sequence detection, the decoding of asynchronous empty time-code-least mean-square error, asynchronous empty time-code-least mean-square error decision-feedback decoding of the present invention, 6 kinds of patterns of asynchronous empty time-code-Maximum likelihood sequence detection of the present invention, average error rate is carried out to emulation with respect to frequency deviation variance, and result as shown in Figure 7.

From Fig. 7: the ber curve of the asynchronous empty time-code-least mean-square error decision-feedback decoding of the present invention is starkly lower than the ber curve that decoding forwardings-least mean-square error decision-feedback is decoded, in the situation that normalization frequency deviation variance is identical, the error rate of asynchronous empty time-code-least mean-square error decision-feedback coding/decoding method is lower, can improve the reliability of system and improve the Outage probability of distributed antenna of system.

Claims (5)

1. an asynchronous empty time-code decoding method in cooperative multipoint transmission, comprises the steps:

(1) system initialization: subscriber equipment adopts least mean-square error channel estimation methods, respectively channel parameter information, time delay information and the frequency offset information between estimating user equipment and multiple different far-end wireless device; Information obtained above is fed back to corresponding far-end wireless device by subscriber equipment;

(2) structure time delay convolutional encoding matrix:

2a) far-end wireless device utilizes alternative manner to calculate translation full rank polynomial sequence: { P ₁(x), P ₂(x), P _r(x) ... P _r(x) } wherein, P _r(x) be the translation full rank multinomial at r far-end wireless device place, the number that R is far-end wireless device, meets R > 1, r=1 ... R;

2b) to above-mentioned { P ₁(x), P ₂(x) ... P _r(x) } translation full rank polynomial sequence is normalized, and obtains the translation full rank polynomial sequence after normalization:

$\{P_1\left(x\right)/\sqrt{R},P_2\left(x\right)/\sqrt{R},P_r\left(x\right)/\sqrt{R}\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;,P_R\left(x\right)/\sqrt{R}\},$

Wherein, it is the normalization translation full rank multinomial at r far-end wireless device place;

2c) in the translation full rank polynomial sequence after normalization $\{P_1\left(x\right)/\sqrt{R},P_2\left(x\right)/\sqrt{R},P_r\left(x\right)/\sqrt{R}\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;\&CenterDot;,P_R\left(x\right)/\sqrt{R}\}$ Each multinomial write corresponding x power coefficient as one dimension code word matrix form according to high order power to the order of low order power, wherein, the coefficient null representation of default x power, obtains the one dimension code word matrix at r far-end wireless device place:

${\stackrel{\&OverBar;}{t}}^{\left(r\right)}=[{{\stackrel{\&OverBar;}{t}}_U}^{\left(r\right)},{{\stackrel{\&OverBar;}{t}}_{U-1}}^{\left(r\right)},\&CenterDot;\&CenterDot;\&CenterDot;{{\stackrel{\&OverBar;}{t}}_1}^{\left(r\right)}],$

Wherein, U is the length of one dimension code word matrix, meets U=R-1, for multinomial middle x power is the corresponding coefficient of i-1, i=1 ... U;

2d) according to the one dimension code word matrix at r far-end wireless device place obtain the convolutional encoding matrix at r far-end wireless device place

Wherein, convolutional encoding matrix for N × (N+U-1) dimension matrix, N is the number that eNodeB evolved base station sends symbol sebolic addressing;

2e) to convolutional encoding matrix use the method for zero padding, obtain the time delay convolutional encoding matrix of r far-end wireless device

${\hat{T}}^{\left(r\right)}=\left[\begin{array}{ccc}{0}_{N\&times;{\mathrm{\&tau;}}_r}& {\stackrel{\&OverBar;}{T}}^{\left(r\right)}& 0_{N\&times;({\mathrm{\&tau;}}_{\max }-{\mathrm{\&tau;}}_r)}\end{array}\right],$

Wherein, time delay convolutional encoding matrix for N × (N+U-1+ τ _max) dimension matrix, for N × τ _rthe full null matrix of dimension, for N × (τ _max-τ _r) dimension full null matrix, τ _rbe the time delay between r far-end wireless device and subscriber equipment, τ _max=max{ τ ₁... τ _r;

(3) subscriber equipment is estimated far-end wireless device entirety equivalent channel matrix

(4) subscriber equipment is constructed the frequency shift (FS) matrix of different far-end wireless device to subscriber equipment:

Wherein, frequency shift (FS) matrix e _rfor M × M ties up matrix, T _sfor mark space, M is time delay convolutional encoding matrix columns, i.e. M=(N+U-1+ τ _max), f _rbe the frequency shift (FS) between r far-end wireless device and subscriber equipment, j is imaginary number unit, and k gets positive integer arbitrarily, and π is constant 3.14, and e is constant 2.71828183;

(5) eNodeB evolved base station sends symbol sebolic addressing S=[s to all far-end wireless device simultaneously ₀, s ₁, s _β..., s _n-1], wherein, s _βrepresent the symbol that different time-gap sends, meet β=0 ..., N-1; (6) different far-end wireless device are all to the symbol sebolic addressing S=[s receiving ₀, s ₁... .., s _n-1] carry out Space Time Coding, the Space Time Coding sequence that each far-end wireless device place sends is:

$Q_r={\left[{\hat{T}}^{\left(r\right)}\right]}^T{S}^T,$

Wherein, [] ^trepresent transposition computing, be r far-end wireless device time delay convolutional encoding matrix;

(7) subscriber equipment receives Space Time Coding sequence Q _rand utilize frequency shift (FS) matrix e _rit is carried out to frequency compensation, obtain the symbol sebolic addressing y after subscriber equipment frequency compensation, wherein, r=1 ... R;

(8) subscriber equipment to frequency compensation after symbol sebolic addressing y, utilize least mean-square error decision-feedback coding/decoding method to decode.

2. asynchronous empty time-code decoding method in cooperative multipoint transmission according to claim 1, wherein step 2a) described far-end wireless device utilizes alternative manner to calculate translation full rank polynomial sequence: { P ₁(x), P ₂(x) ... P _r(x) }, carry out as follows:

2.1) iterations n is initialized as to 1, translation full rank polynomial sequence is initialized as to { P ₁(x)=1};

2.2) make iterations n from increasing 1, the translation full rank polynomial sequence { P while judging iterations n-1 ₁(x), P ₂(x) ... P _n-1(x) P } ₁(x), P ₂(x) ... P _n-1(x) greatest common divisor between, if greatest common divisor GCD is 1, execution step 2.2a); If greatest common divisor GCD is u (x), wherein u (x) is not equal to 1, execution step 2.2b);

2.2a) select two multinomial q ₂(x) and meet q ₂(x) aliquant wherein multinomial q ₂(x) be any multinomial that the highest power number is 1, multinomial that the highest power number is any multinomial of n-1, according to { P ₁(x), P ₂(x) ... P _n-1(x) }, q ₂(x) and translation full rank polynomial sequence while obtaining iterations n $\{P_1\left(x\right),P_2\left(x\right),\&CenterDot;\&CenterDot;\&CenterDot;P_{n-1}\left(x\right),P_n\}=\{q_2\left(x\right)P_1\left(x\right),q_2\left(x\right)P_2\left(x\right),\&CenterDot;\&CenterDot;\&CenterDot;q_2\left(x\right)P_n\left(x\right),{\hat{q}}_n\left(x\right)\};$

2.2b) select two multinomial q ₂(x) and meet q ₂(x) aliquant wherein multinomial q ₂(x) be any multinomial that the highest power number is 1, multinomial that the highest power number is any multinomial of n-1, according to { P ₁(x), P ₂(x) ... P _n-1(x) }, q ₂(x) and translation full rank polynomial sequence while obtaining iterations n $\{P_1\left(x\right),P_2\left(x\right),\&CenterDot;\&CenterDot;\&CenterDot;P_{n-1}\left(x\right),P_n\}=\{P_1\left(x\right)P_2\left(x\right),\&CenterDot;\&CenterDot;\&CenterDot;P_n\left(x\right),{\hat{q}}_n\left(x\right)\};$

2.3) judge whether iterations n equals R, if iterations n=R obtains translation full rank polynomial sequence { P corresponding to all far-end wireless device ₁(x), P ₂(x) ... P _r(x) }; If iterations n < is R, carry out above-mentioned steps 2.2).

3. asynchronous empty time-code decoding method in cooperative multipoint transmission according to claim 1, wherein the described subscriber equipment of step (3) is estimated far-end wireless device entirety equivalent channel matrix carry out as follows:

3a) eNodeB evolved base station sends the known training sequence A=[A of subscriber equipment to all far-end wireless device ₀, A ₁, A _α..., A _n-1], wherein A _αrepresent the symbol that different time-gap sends, α=0 ..., N-1;

3b) different far-end wireless device are carried out Space Time Coding to the training sequence A receiving, and obtain Space Time Coding training sequence W _r:

$W_r={\left[{\hat{T}}^{\left(r\right)}\right]}^T{A}^T,$

Wherein, Space Time Coding training sequence W _rdimension be M × 1 dimension, [] ^trepresent transposition computing, be the time delay convolutional encoding matrix of r far-end wireless device, r=1 ... R;

3c) different far-end wireless device are by Space Time Coding training sequence W _rsend to subscriber equipment, obtain subscriber equipment and receive training symbol sequence

$\begin{array}{c}\tilde{y}={\left[\begin{array}{ccccc}{h}_1{W_1}^T& h_2{W_2}^T& h_r{W_r}^T& \&CenterDot;\&CenterDot;\&CenterDot;& h_R{W_R}^T\end{array}\right]}^T+I\\ ={\left[\begin{array}{ccccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& h_r{\hat{T}}^{\left(r\right)}& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T{A}^T+I\end{array}$

Wherein, I is the noise matrix of MR × 1 dimension, h _rit is the channel parameter information between r far-end wireless device and subscriber equipment;

3d) subscriber equipment utilizes known training sequence A=[A ₀, A ₁... .., A _n-1], and apply least mean-square error channel estimation methods subscriber equipment is received to training symbol sequence carry out channel estimating, obtain far-end wireless device entirety equivalent channel matrix:

$\hat{H}={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T.$

4. asynchronous empty time-code decoding method in cooperative multipoint transmission according to claim 1, wherein the described subscriber equipment of step (7) receives Space Time Coding sequence Q _rand utilize frequency shift (FS) matrix e _rit is carried out to frequency compensation, carries out as follows:

4a) different far-end wireless device are by Space Time Coding sequence Q _rsend to subscriber equipment, obtain subscriber equipment receiving symbol sequence

$\begin{array}{c}\hat{y}={\left[\begin{array}{cccc}{h}_1{Q_1}^T& h_2{Q_2}^T& \&CenterDot;\&CenterDot;\&CenterDot;& h_R{Q_R}^T\end{array}\right]}^T+n\\ ={\left[\begin{array}{cccc}{h}_1\left({\hat{T}}^{\left(1\right)}\right)& h_2\left({\hat{T}}^{\left(2\right)}\right)& \&CenterDot;\&CenterDot;\&CenterDot;& h_R\left({\hat{T}}^{\left(R\right)}\right)\end{array}\right]}^T{S}^T+n=\hat{H}{S}^T+n\end{array}$

Wherein, for far-end wireless device entirety equivalent channel matrix, h _rbe the channel parameter information between r far-end wireless device and subscriber equipment, n is the noise matrix of MR × 1 dimension, [] ^trepresent transposition computing;

4b) subscriber equipment utilizes frequency shift (FS) matrix frequency shift (FS) matrix e _rto subscriber equipment receiving symbol sequence carry out frequency compensation, obtain the symbol sebolic addressing after subscriber equipment frequency compensation:

$y=\left[\begin{array}{cccc}{e}_1& e_2& \&CenterDot;\&CenterDot;\&CenterDot;& e_R\end{array}\right]\hat{H}{S}^T+\left[\begin{array}{cccc}{e}_1& e_2& \&CenterDot;\&CenterDot;\&CenterDot;& e_R\end{array}\right]n={\mathrm{HS}}^T+\hat{n}$

Wherein, the dimension of y is M × 1 dimension, for the equivalent channel matrix after frequency compensation, for the noise matrix of M × 1 dimension.

5. asynchronous empty time-code decoding method in cooperative multipoint transmission according to claim 1, the wherein symbol sebolic addressing y after the subscriber equipment frequency compensation described in step (8), utilize least mean-square error decision-feedback coding/decoding method to decode, carry out as follows:

5a) utilize the equivalent channel matrix H structure companion matrix R after frequency compensation:

$R=H^{H}H+\frac{{\mathrm{\&sigma;}}_n^2}{{\mathrm{\&sigma;}}_s^2}{I}_N$

Wherein, the dimension of R is N × N, [] ^hrepresent conjugate transpose computing, for the variance of each element in noise matrix n, for sending symbol sebolic addressing S=[s ₀, s ₁... .., s _n-1] power, I _nfor the unit matrix of N × N dimension;

5b) above-mentioned companion matrix R is carried out to Cholesky decomposition:

R＝LDL ^H

Wherein, L is that diagonal entry is 1 lower triangular matrix, represent the conjugate transpose of L, D is the diagonal matrix of N × N dimension;

5c) utilizing above-mentioned diagonal entry is 1 lower triangular matrix L and companion matrix R, constructs respectively rear end feedback filtering matrix B and front end feedback filtering matrix F:

$B=L-I_N=\left[\begin{array}{c}{b}_0\\ b_1\\ b_g\\ .\\ .\\ .\\ b_{N-1}\end{array}\right]$

F＝LR ^-1H ^H

Wherein, the dimension of B is N × N, I _nfor the unit matrix of N × N dimension, b _gbe the row vector of 1 × N dimension, g=0 ..., N-1, the dimension of F is N × N, H ^hrepresent the conjugate transpose of H, [] ^-1represent to get inverse operation, R ^-1expression companion matrix R's is contrary;

The symbol sebolic addressing y that 5d) utilizes above-mentioned front end feedback filtering matrix F to carry out after frequency compensation subscriber equipment carries out forward direction filtering, obtains the filtered vector Z of forward direction:

Z＝Fy＝[z ₀,z ₁,z _γ…z _N-1] ^T；

Wherein, the dimension of Z is N × 1 dimension N × N, z _γrepresent γ element in the filtered vector Z of forward direction, γ=0 ..., N-1;

5e) according to above-mentioned rear end feedback filtering matrix B and the filtered vector Z of forward direction, realize the decoding to information sequence according to formula below:

Wherein, be illustrated in modulation constellation and find and symbol z ₀the constellation point of Euclidean distance minimum be illustrated in modulation constellation and find and symbol the constellation point of Euclidean distance minimum z _jrepresent forward direction filtered vector Z=[z ₀, z ₁z _n-1] ^tin j element, represent j × 1 dimensional decoding symbolic vector, b ^* _jfor the capable b of j+1 in the feedback filtering matrix B of rear end _jfront j+1 row.