CN104113398A - MIMO blind channel estimation fuzziness removal method based on orthogonal space-time block codes - Google Patents

Abstract

The invention discloses an MIMO blind channel estimation fuzziness removal method based on orthogonal space-time block codes. The method includes the following steps: establishing an MIMO space-time system to analyze training sequence signals; before emission, grouping and processing data signals and utilizing jointly a blind and training-sequence-based channel estimation method to carry out blind channel estimation on a first data block; and adopting a signal and channel joint two-dimension search on the first data block to carry out maximum likelihood decoding and using a training sequence estimation value obtained through zero forcing equalization to carry out training-sequence-based channel estimation on follow-up data blocks and then adopting sent-signal one-dimension search on the follow-up data blocks to carry out maximum likelihood decoding. The beneficial effects of the method are that signal and channel joint two-dimension search is adopted and inter-signal correlation in the orthogonal space-time codes is utilized to eliminate inherent phase fuzziness of a channel estimation result on the basis of blind channel estimation so that the range of channel possible solutions is reduced and convenience is provided to determination of phases of decoded signals.

Description

MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code

Technical field

The present invention relates to a kind of MIMO blind Channel Estimation ambiguity removal method, be specifically related to a kind of MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code, belong to wireless communication technology field.

Background technology

Channel estimating refers to that receiving terminal obtains process and the method for channel condition information.Because channel equalization and the decoding of receiving terminal need known channel state information just can complete conventionally, therefore the accuracy of channel estimating is having a strong impact on the transmission quality of receptivity and data, also makes the estimation of wireless channel and identification become an important field of research in wireless communication signals processing.Traditional channel estimating is generally by project training sequence or insert pilot tone and realize channel estimating in packet, and the shortcoming of these methods is significantly to have reduced channel capacity and the availability of frequency spectrum.Although for quasi-static channel opens, this loss is very little, but in high-speed radiocommunication, when channel is, becomes, and this loss just be can not ignore.In addition, in cooperative communication system, receiving terminal is under the condition of guarantee and transmitting terminal effective cooperation, known all or part of training sequence, can adopt the channel estimating of non-blind or half-blindness, and in non-cooperative communication system, the content of training sequence transmitting terminal being adopted due to receiving terminal is completely unknown, in order to realize the detection of MIMO signal, must utilize blind channel estimation method to obtain channel condition information.

In the blind Channel Estimation problem of mimo system, only realizing the complete identification of channel matrix according to observation signal and the recovery of source signal cannot realize, there is certain ambiguity in the channel response value obtaining and actual interchannel.Ambiguity under SIMO system is a scalar factor, only there is amplitude and phase ambiguity, under mimo system, ambiguity shows as a matrix, comprise order ambiguity, phase ambiguity and amplitude ambiguity, estimate that the channel order in the different antennae that obtains misplaces, and make the overall convergent-divergent in rotation and the amplitude of signal constellation (in digital modulation) figure that equilibrium obtains and original constellation generation phase place.For the communication system of permanent mould modulation, amplitude is fuzzy not to exert an influence to input, if but fuzzy order and phase ambiguity can not be removed, have a strong impact on the detection of signal.In existing algorithm, the general rectification that is all insertion portion training sequence or pilot tone are carried out channel estimation value solves ambiguity problem, but under signal blind Detecting scene, receiving terminal cannot be known training sequence or pilot tone, so the problem of ambiguity is the difficult point greatly of one in blind Channel Estimation.

For the blind Channel Estimation problem of mimo system, people have proposed many solutions based on time domain or frequency domain.Subspace method is as the representative of time domain approach, simple in structure and functional because of it, has been subject to research widely.Gao F, the people such as Nallanathan A have proposed a kind of Blind channel estimation algorithm based on subspace at article " Subspace-based blind channel estimation for SISO; MISO and MIMO-OFDM systems ", and utilize pre-coding matrix to solve ambiguity problem.But in non-cooperative communication, the pre-coding matrix design of making a start, is unknown to receiving terminal, thus the method cannot solution the ambiguity problem in cooperation MIMO communication by no means.

The people such as Binning Chen have proposed a kind of frequency domain channel estimation method that receives signal second order and high-order statistic that utilizes in " Frequency domain blind MIMO system identification based on second and higher order statistics ", and ambiguity problem is studied, therefore by after many articles quote to process ambiguity problem.But this algorithm can only be unified into the phase place deflection of channel estimation value and the value of frequency-independent, that is to say and still have unknown phase ambiguity, this ambiguity need to utilize real channel to proofread and correct.In non-cooperative communication, actual channel information is unknown, so the method can not be applied to the blind Channel Estimation of non-cooperative communication.

In STBC-MIMO system, the information providing by Space Time Coding, can necessarily process the ambiguity of blind Channel Estimation.The people such as Choqueuse V have proposed a kind of channel estimation methods that utilizes high-order statistic in " Blind channel estimation for STBC systems using higher-order statistics ", and utilize STBC coded message, the channel estimating ambiguity matrix of the system that uses several specific patterns is limited in a set, but still can not accurately determine ambiguity matrix, therefore the method also cannot solution cooperative communication system by no means in the ambiguity problem of blind Channel Estimation.

Summary of the invention

For solving the deficiencies in the prior art, the object of the present invention is to provide a kind of MIMO blind Channel Estimation ambiguity removal method, the method is based on Orthogonal Space-Time Block Code (Orthogonal Space-Time Block Code, OSTBC), can efficient solution the ambiguity problem of blind Channel Estimation in cooperation MIMO communication by no means.

In order to realize above-mentioned target, the present invention adopts following technical scheme:

A kind of MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code, is characterized in that, comprises the following steps:

(1), set up, analyze and process MIMO space-time system model:

(1) set up one and there is N _tindividual transmitting antenna and N _rthe MIMO space-time system of individual reception antenna, each frame signal of transmission antennas transmit is made up of training sequence, Cyclic Prefix and data three parts, and aforementioned training sequence is time domain orthogonal training sequence, and channel is smooth slow change rayleigh fading channel, supposes continuous N _fthe channel status of frame signal experience is identical;

(2) analyze time domain orthogonal training sequence signal:

Suppose the time domain orthogonal training sequence signal N of k arbitrary antenna of moment _t× 1 dimension complex vector s _tr(k) represent, receive signal indication and be:

y _tr(k)＝Hs _tr(k)+v(k)

In formula, H is N _r× N _tdimension rayleigh fading channel response matrix, y _tr(k) be N _r× 1 dimension received signal vector, v (k) is N _r× 1 dimension noise vector, aforementioned noise obeys that average is 0, variance is gaussian Profile;

(3) before transmitting, data-signal is divided into groups:

Make s (k)=[s ₁(k) s ₂(k) ... s _n(k)] ^tfor armed k the packet being formed by N symbol, and each symbol independent same distribution;

(4) process k packet s (k):

S (k) is mapped as to N through Space Time Coding _t× L dimension encoder matrix C (k):

$C\left(k\right)=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}(A_n{s}_{\mathrm{Rn}}\left(k\right)+j{B}_n{s}_{\mathrm{In}}\left(k\right))$

In formula, A _nand B _nbe respectively corresponding to n symbol s _n(k) real part (s _rn) and imaginary part (s (k) _in(k) encoder matrix), L is the number of encoder matrix time slot, receives signal indication to be:

Y(k)＝HC(k)+V(k)

In formula, Y (k) is N _r× L dimension receives signal matrix, and V (k) is N _r× L ties up noise matrix, and Y (k), V (k) obey that average is 0, variance is gaussian Profile;

(2), channel estimating and decoding:

(1) export the estimated signal of first data block:

First, combine and utilize channel estimation methods blind and based on time domain orthogonal training sequence, first data block is carried out to blind Channel Estimation; Then, adopt signal and channel associating two-dimensional search to do maximum likelihood decoding to first data block, export the estimated signal of first data block;

(2) estimated signal of output subsequent data blocks:

First, utilize the time domain orthogonal training sequence estimated value that zero forcing equalization obtains to carry out the channel estimating based on time domain orthogonal training sequence to subsequent data blocks, make the estimation channel of subsequent data blocks there is the phase ambiguity identical with first data block; Then, adopt transmitted signal linear search to do maximum likelihood decoding to subsequent data blocks, the estimated signal of output subsequent data blocks.

The aforesaid MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code, is characterized in that, in the time that first data block is carried out to blind Channel Estimation, utilizes chu sequence to do time domain orthogonal training sequence, adopts Alamouti delivery plan.

The aforesaid MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code, is characterized in that, in the time that first data block is carried out to blind Channel Estimation, utilizes QPSK modulation sequence to do time domain orthogonal training sequence, adopts Alamouti delivery plan.

Usefulness of the present invention is: by adopting signal and channel associating two-dimensional search, utilize the correlation between signal in orthogonal Space Time Coding, on the basis of blind Channel Estimation, eliminate the intrinsic phase ambiguity of channel estimation results, dwindle the scope of channel feasible solution, thereby be that the phase place of determining decoded signal is provided convenience; In addition, this scheme is by utilizing respectively channel estimation methods blind and based on time domain orthogonal training sequence at different pieces of information piece, by phase deviation unification to fixed value of the different pieces of information piece decoded data once sending, solve the problem that causes decoding error in non-cooperative communication due to the ambiguity problem of blind Channel; Method of the present invention can be applied to various multi-antenna signals, the blind identification of collaboration communication signal, blind Detecting.

Brief description of the drawings

Fig. 1 sends information structure diagram;

Fig. 2 is channel estimating and decoding process figure;

Fig. 3 is the maximum likelihood decoding flow chart of the first frame;

Fig. 4 is the maximum likelihood decoding flow chart of subsequent frame;

Fig. 5 is chu sequence as time domain orthogonal training sequence, while adopting Alamouti delivery plan, system receives the planisphere of signal;

Fig. 6 is chu sequence as time domain orthogonal training sequence, while adopting Alamouti delivery plan, the planisphere of system equalization signal;

Fig. 7 is chu sequence during as time domain orthogonal training sequence, the decoding performance curve of Alamouti delivery plan;

Fig. 8 is QPSK modulation sequence as time domain orthogonal training sequence, while adopting Alamouti delivery plan, system receives the planisphere of signal;

Fig. 9 is QPSK modulation sequence as time domain orthogonal training sequence, while adopting Alamouti delivery plan, the planisphere of system equalization signal;

Figure 10 is QPSK modulation sequence during as time domain orthogonal training sequence, the decoding performance curve of Alamouti delivery plan;

Figure 11 is QPSK modulation sequence during as time domain orthogonal training sequence, the comparison diagram of the decoding performance of the system that Alamouti delivery plan and channel information are completely known.

Embodiment

Below in conjunction with the drawings and specific embodiments, the present invention is done to concrete introduction.

One, set up, analyze and process MIMO space-time system model

1, set up MIMO space-time system model

Set up one and there is N _tindividual transmitting antenna and N _rthe MIMO space-time system of individual reception antenna, each frame signal of transmission antennas transmit is made up of training sequence, Cyclic Prefix and data three parts, and channel is smooth slow change rayleigh fading channel, supposes continuous N _fthe channel status of frame signal experience is identical, and a data block is by N _fframe composition, as shown in Figure 1.

Training sequence in wireless communication system is divided into time domain orthogonal training sequence, frequency domain quadrature training sequence and code territory quadrature training sequence, and in the space-time system model of setting up in the present invention, training sequence adopts time domain orthogonal training sequence.

2, analyze time domain orthogonal training sequence signal

Suppose the time domain orthogonal training sequence signal N of k arbitrary antenna of moment _t× 1 dimension complex vector s _tr(k) represent, receive signal indication and be:

y _tr(k)＝Hs _tr(k)+v(k)

In formula, H is N _r× N _tdimension rayleigh fading channel response matrix, y _tr(k) be N _r× 1 dimension received signal vector, v (k) is N _r× 1 dimension noise vector, wherein, noise obeys that average is 0, variance is gaussian Profile.

3, process MIMO space-time system model

Data-signal, because needs carry out Space Time Coding, therefore first divided into groups before transmitting, makes s (k)=[s ₁(k) s ₂(k) ... s _n(k)] ^tfor armed k the packet being formed by N symbol, and each symbol independent same distribution.

Next process k packet s (k), concrete, s (k) is mapped as to N through Space Time Coding _t× L dimension encoder matrix C (k):

$C\left(k\right)=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}(A_n{s}_{\mathrm{Rn}}\left(k\right)+j{B}_n{s}_{\mathrm{In}}\left(k\right))$

In formula, A _nand B _nbe respectively corresponding to n symbol s _n(k) real part (s _rn) and imaginary part (s (k) _in(k) encoder matrix), L is the number of encoder matrix time slot.Receiving signal can be expressed as:

Y(k)＝HC(k)+V(k)

In formula, Y (k) is N _r× L dimension receives signal matrix, and V (k) is N _r× L ties up noise matrix, and Y (k), V (k) obey that average is 0, variance is gaussian Profile.

In addition,, because channel becomes slowly, the channel of adjacent data block n+1 and data block n is followed following relation:

$H_{n+1}=\sqrt{1-\mathrm{\β}}\·H_n+\sqrt{\mathrm{\β}}\·\mathrm{\ΔH}$

H _nobey multiple Gaussian Profile with △ H, β is constant coefficient, and the less channel variation of β value is less.

Two, channel estimating and decoding

In Blind channel estimation algorithm in the past, the phase ambiguity that each channel estimating produces is not identical and be random, and this brings very large difficulty to being correctly decoded.

Next,, with reference to Fig. 2, introduce in detail channel estimating involved in the present invention and decoding scheme.

1, first data block is carried out to channel estimating and decoding

Channel estimating part: combine and utilize channel estimation methods blind and based on time domain orthogonal training sequence, first data block is carried out to blind Channel Estimation, by phase ambiguity unification to fixed value of first data block, this fixed value is determined by semanteme judgement.

Decoded portion: due to the intrinsic ambiguity of blind Channel Estimation, channel estimating exists many groups to separate.The present invention combines two-dimensional search in decoded portion by employing signal and channel, utilize the correlation between signal in Space Time Coding, first data block is done to maximum likelihood decoding, on the basis of channel estimating, further dwindle the scope of channel feasible solution, thereby provide convenience for the definite of final phase ambiguity.

Unified for the decoded signal phase place deflection that all data blocks are caused by blind Channel Estimation ambiguity, we only carry out the two-dimensional search of signal and channel in the maximum likelihood decoding of first data block, and detailed process is shown in Fig. 3.

When first data block is carried out to blind Channel Estimation, because this blind Channel Estimation is utilized time domain orthogonal training sequence and completed, and for different time domain orthogonal training sequences, the performance of scheme exists difference.

Processing scheme while having there is in recent years numerous multi-antenna space for different communication environment.Wherein, Space-Time Block Coding (STBC) scheme, by providing diversity gain improve connective stability and improve data transmission rate, is scheme while having representational sky.But its performance depends on the accuracy of channel estimating to a great extent.

Taking classical Alamouti scheme as example, its encoder matrix can be expressed as $C_{\mathrm{STBC}}=\left[\begin{array}{cc}{s}_1& -s_2^{*}\\ s_2& s_1^{*}\end{array}\right].$ Therefore, below we will be taking two transmitting antennas as example, the channel estimating and the decoding problem that are done the Alamouti delivery plan of time domain orthogonal training sequence by chu sequence and QPSK modulation sequence are discussed respectively.

(1), utilize chu sequence as time domain orthogonal training sequence

In the time not considering noise, there is the phase ambiguity of 180 ° or 0 ° in whole mimo system channel matrix.Concrete derivation is as follows:

Make h ₁, h ₂represent respectively the true subchannel of two transmit antennas, s ₁, s ₂represent actual transmission signal, receive signal and be:

$\left[\begin{array}{cc}{h}_1& h_2\end{array}\right]\left[\begin{array}{cc}{s}_1& -s_2^{*}\\ s_2& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}{h}_1{s}_1+h_2{s}_2& -h_1{s}_2^{*}+h_2{s}_1^{*}\end{array}\right]$

Order represent channel estimation value, represent final decoded result, if the subchannel estimated value of two antennas all exists 180 ° of phase place deflections, while decoding with such channel, we can obtain:

$\left[\begin{array}{cc}\stackrel{^^}{h_1}& h_2\end{array}\right]\left[\begin{array}{cc}\stackrel{^^}{s_1}& -s_2^{*}\\ \stackrel{^^}{s_2}& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}-h_1\stackrel{^^^^}{s_{1-}}{h}_2{s}_2& h_1{s}_2^{*}-h_2{s}_1^{*}\end{array}\right]$

Order α ₁=α ₂=-1, result is identical with reception signal, and error vector is 0, therefore in the case, 180 ° of phase place deflections can occur decoded signal.

From deriving, for Alamouti delivery plan, decoded portion has certain selection effect to phase ambiguity, makes final decoded result only may have two kinds, is respectively (s ₁s ₂) and (s ₁-s ₂), wherein, (s ₁s ₂) be correct decoding.

(2), utilize QPSK modulation sequence to do time domain orthogonal training sequence

In the time not considering noise, there is the phase ambiguity of 0 °, 180 °, 90 ° or-90 ° in whole mimo system channel matrix.Concrete derivation is as follows:

Make h ₁, h ₂represent respectively the true subchannel of two transmit antennas, s ₁, s ₂represent actual transmission signal, receive signal and be:

$\left[\begin{array}{cc}{h}_1& h_2\end{array}\right]\left[\begin{array}{cc}{s}_1& -s_2^{*}\\ s_2& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}{h}_1{s}_1+h_2{s}_2& -h_1{s}_2^{*}+h_2{s}_1^{*}\end{array}\right]$

Order represent channel estimation value, represent final decoded result, while decoding with such channel, α ₁with α ₂respectively desirable 1 ,-1, i or-i, remove and be correctly decoded (α ₁=α ₂=1) situation, we need to consider to also have three kinds of situations:

If 1. the subchannel estimated value of two antennas all exists 180 ° of phase place deflections, we can obtain:

$\left[\begin{array}{cc}\stackrel{^^}{h_1}& h_2\end{array}\right]\left[\begin{array}{cc}\stackrel{^^}{s_1}& -s_2^{*}\\ \stackrel{^^}{s_2}& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}-h_1\stackrel{^^^^}{s_{1-}}{h}_2{s}_2& h_1{s}_2^{*}-h_2{s}_1^{*}\end{array}\right]$

Order α ₁=α ₂=-1, result is identical with reception signal, and error vector is 0, therefore in the case, 180 ° of phase place deflections can occur decoded signal.

If 2. first subchannel estimated value exists 90 ° of phase place deflections, there are-90 ° of phase place deflections in the second sub-channels estimated value, and we can obtain:

$\left[\begin{array}{cc}{\mathrm{ih}}_1& -{\mathrm{ih}}_2\end{array}\right]\left[\begin{array}{cc}\stackrel{^^}{s_1}& -s_2^{*}\\ \stackrel{^^}{s_2}& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}{\mathrm{ih}}_1\stackrel{^^^^}{s_{1-}}{\mathrm{ih}}_2{s}_2& -{\mathrm{ih}}_1{s}_2^{*}-{\mathrm{ih}}_2{s}_1^{*}\end{array}\right]$

Order α ₁=-i, α ₂=i, result is identical with reception signal, and error vector is 0, and therefore in the case, there are-90 ° of phase place deflections in the decoded signal of antenna 1, and there are 90 ° of phase place deflections in the decoded signal of antenna 2.

If 3. first subchannel estimated value exists-90 ° of phase place deflections, there are 90 ° of phase place deflections in the second sub-channels estimated value, and we can obtain:

$\left[\begin{array}{cc}-{\mathrm{ih}}_1& {\mathrm{ih}}_2\end{array}\right]\left[\begin{array}{cc}\stackrel{^^}{s_1}& -s_2^{*}\\ \stackrel{^^}{s_2}& s_1^{*}\end{array}\right]=\left[\begin{array}{cc}-{\mathrm{ih}}_1\stackrel{^^^^}{s_{1+}}{\mathrm{ih}}_2{s}_2& {\mathrm{ih}}_1{s}_2^{*}+{\mathrm{ih}}_2{s}_1^{*}\end{array}\right]$

Order α ₁=i, α ₂=-i, result is identical with reception signal, and error vector is 0, and therefore in the case, there are 90 ° of phase place deflections in the decoded signal of antenna 1, and there are-90 ° of phase place deflections in the decoded signal of antenna 2.

To sum up aforementioned, in the time using QPSK modulation sequence, as time domain orthogonal training sequence, Alamouti delivery plan is carried out to channel estimating and decoding, decoded result has following four kinds of possibilities: (s ₁s ₂), (s ₁-s ₂), (is ₁is ₂), (is ₁-is ₂).

2, subsequent data blocks is carried out to channel estimating and decoding

Channel estimating part: utilize the time domain orthogonal training sequence estimated value that zero forcing equalization obtains to carry out the channel estimating based on time domain orthogonal training sequence to subsequent data blocks, make the estimation channel of subsequent data blocks there is the phase ambiguity identical with first data block, thereby by phase ambiguity unification to fixed value of the different pieces of information piece once sending.

Decoded portion: adopt transmitted signal linear search to do maximum likelihood decoding to subsequent data blocks, the estimated signal of output subsequent data blocks.

Visible, further determining (after first data block being carried out to channel estimating and decode) after channel, what to the decoding of subsequent data blocks, we adopted is general maximum likelihood algorithm, adopt transmitted signal linear search to do maximum likelihood decoding, thereby ensured that the phase place deflection that different pieces of information piece decoded signal carries is identical, this detailed process is shown in Fig. 4.

Three, scheme emulation and performance evaluation

In order to obtain estimated performance, we use respectively the time domain orthogonal training sequence being made up of chu sequence and the time domain orthogonal training sequence being made up of QPSK modulation sequence, estimate channel by direct SVD decomposition method, and phase ambiguity is eliminated with real channel, the statistics error rate, result is specific as follows:

1, chu sequence is as time domain orthogonal training sequence, employing Alamouti delivery plan

Simulated conditions: set up one and there are two the eight MIMO space-time systems of receiving, adopt Alamouti delivery plan, send and receive two data blocks, each data block 4 frames.Send time domain orthogonal training sequence in data and use chu sequence, be made up of 32 symbols, data division is made up of 64 symbols.Carry out altogether Monte Carlo simulation 1000 times.

The planisphere that receives signal is shown in Fig. 5.

The planisphere of equalizing signal is shown in Fig. 6.

Decoding performance curve chart is shown in Fig. 7.

As can be seen here: use chu sequence as time domain orthogonal training sequence, under Alamouti space time coding scheme, the algorithm of carrying equilibrium be preferably subject to channel effect to be aliasing in reception signal together, thereby correctly recover system transmitted signal, and the error rate reduces with the increase of signal to noise ratio, reaches 10 at 12dB ^-2.

2, QPSK modulation sequence is as time domain orthogonal training sequence, employing Alamouti delivery plan

Simulated conditions: set up one and there are two the eight MIMO space-time systems of receiving, adopt Alamouti delivery plan, send and receive two data blocks, each data block 4 frames.Send time domain orthogonal training sequence in data and use QPSK modulation sequence, be made up of 32 symbols, data division is made up of 64 symbols.Carry out altogether Monte Carlo simulation 1000 times, the statistics error rate.

The planisphere that receives signal is shown in Fig. 8.

The planisphere of equalizing signal is shown in Fig. 9.

Decoding performance curve chart is shown in Figure 10.

As can be seen here: use QPSK modulation sequence as time domain orthogonal training sequence, under Alamouti space time coding scheme, the algorithm of carrying equilibrium be preferably subject to channel effect to be aliasing in reception signal together, thereby correctly recover system transmitted signal, and the error rate reduces with the increase of signal to noise ratio, reaches 10 at 15dB ^-2.

While utilizing QPSK modulation sequence as time domain orthogonal training sequence, the decoding performance of the decoding performance of Alamouti delivery plan and the complete known system of channel information is compared, see Figure 11.

As can be seen here: under the scene of considering at this patent, receiving terminal cannot be known time domain orthogonal training sequence particular content and channel condition information, therefore under the bit error rate performance of blind Channel Estimation and decoding and cooperative communication scene, the bit error rate performance that known real channel is decoded has certain gap, but also can realize to a certain extent system proper communication.

To sum up aforementioned, method of the present invention is first by adopting signal and channel associating two-dimensional search, utilize the correlation between signal in Space Time Coding, on the basis of blind Channel Estimation, eliminate the intrinsic phase ambiguity of channel estimation results, dwindle the scope of channel feasible solution, thereby be that the phase place of determining decoded signal is provided convenience.

In addition, the solution of the present invention is by utilize respectively channel estimation methods blind and based on time domain orthogonal training sequence at different pieces of information piece, by phase deviation unification to fixed value of the different pieces of information piece decoded data once sending.

Generally speaking, method of the present invention has solved the impact that the intrinsic phase ambiguity of blind Channel Estimation causes system decodes.

Method of the present invention can be applied to various multi-antenna signals, the blind identification of collaboration communication signal, blind Detecting.

It should be noted that, above-described embodiment does not limit the present invention in any form, and all employings are equal to replaces or technical scheme that the mode of equivalent transformation obtains, all drops in protection scope of the present invention.

Claims (3)

1. the MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code, is characterized in that, comprises the following steps:

(1), set up, analyze and process MIMO space-time system model:

(1) set up one and there is N _tindividual transmitting antenna and N _rthe MIMO space-time system of individual reception antenna, each frame signal of transmission antennas transmit is made up of training sequence, Cyclic Prefix and data three parts, and described training sequence is time domain orthogonal training sequence, and channel is smooth slow change rayleigh fading channel, supposes continuous N _fthe channel status of frame signal experience is identical;

(2) analyze time domain orthogonal training sequence signal:

Suppose the time domain orthogonal training sequence signal N of k arbitrary antenna of moment _t× 1 dimension complex vector s _tr(k) represent, receive signal indication and be:

y _tr(k)＝Hs _tr(k)+v(k)

In formula, H is N _r× N _tdimension rayleigh fading channel response matrix, y _tr(k) be N _r× 1 dimension received signal vector, v (k) is N _r× 1 dimension noise vector, described noise obeys that average is 0, variance is gaussian Profile;

(3) before transmitting, data-signal is divided into groups:

Make s (k)=[s ₁(k) s ₂(k) ... s _n(k)] ^tfor armed k the packet being formed by N symbol, and each symbol independent same distribution;

(4) process k packet s (k):

S (k) is mapped as to N through Space Time Coding _t× L dimension encoder matrix C (k):

$C\left(k\right)=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}(A_n{s}_{\mathrm{Rn}}\left(k\right)+j{B}_n{s}_{\mathrm{In}}\left(k\right))$

In formula, A _nand B _nbe respectively corresponding to n symbol s _n(k) real part (s _rn) and imaginary part (s (k) _in(k) encoder matrix), L is the number of encoder matrix time slot, receives signal indication to be:

Y(k)＝HC(k)+V(k)

In formula, Y (k) is N _r× L dimension receives signal matrix, and V (k) is N _r× L ties up noise matrix, and Y (k), V (k) obey that average is 0, variance is gaussian Profile;

(2), channel estimating and decoding:

(1) first data block is carried out to channel estimating and decoding:

First, combine and utilize channel estimation methods blind and based on time domain orthogonal training sequence, first data block is carried out to blind Channel Estimation; Then, adopt signal and channel associating two-dimensional search to do maximum likelihood decoding to first data block, export the estimated signal of first data block;

(2) subsequent data blocks is carried out to channel estimating and decoding:

First, utilize the time domain orthogonal training sequence estimated value that zero forcing equalization obtains to carry out the channel estimating based on time domain orthogonal training sequence to subsequent data blocks, make the estimation channel of subsequent data blocks there is the phase ambiguity identical with first data block; Then, adopt transmitted signal linear search to do maximum likelihood decoding to subsequent data blocks, the estimated signal of output subsequent data blocks.

2. the MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code according to claim 1, is characterized in that,

In the time that first data block is carried out to blind Channel Estimation, utilize chu sequence to do time domain orthogonal training sequence, adopt Alamouti delivery plan.

3. the MIMO blind Channel Estimation ambiguity removal method based on Orthogonal Space-Time Block Code according to claim 1, is characterized in that,

In the time that first data block is carried out to blind Channel Estimation, utilize QPSK modulation sequence to do time domain orthogonal training sequence, adopt Alamouti delivery plan.