CN102868434B - A kind of MIMO detection method and device - Google Patents

Abstract

The invention discloses a kind of MIMO detection method and device, relate to the communications field, described method comprises: carry out linearity test to received signal, obtains the first estimated value; Carry out non-linear detection to received signal according to predetermined iterations, obtain the estimated value that corresponding part sends signal; The estimated value sending signal according to the first estimated value and part carries out bit inversion operation to the residue transmission signal that upper step does not obtain estimated value, obtains the estimated value that corresponding residue sends signal; Assembling section sends the estimated value of signal and the estimated value of residue transmission signal, obtains the second estimated value; Obtain vector space according to the first estimated value and the second estimated value, in vector space, carry out Maximum Likelihood Detection to received signal, obtain final estimated value.Described method and device, according to actual channel quality and communication system requirements situation flexible complexity and detection perform, can realize the detection perform of varying level with the detection complexity of different brackets.

Description

A kind of MIMO detection method and device

Technical field

The present invention relates to communication technical field, particularly a kind of MIMO detection method and device.

Background technology

Since middle nineteen nineties in last century, MIMO signal treatment technology becomes the maximum study hotspot of communication theory.MIMO technology is that communication system introduces Spatial Dimension, makes people in time domain, frequency domain and spatial domain combined optimization communication system, thus can likely obtain the performance of convergence and theoretical limit.First practical mimo system is V-BLAST system, and it obtains very high spectrum efficiency under quasistatic (BlockFading) fading channel conditions.Meanwhile, MIMO detection technique obtains the common concern of academia.

MIMO detection algorithm relates to mimo system performance quality and whether its complexity can carry out practical application.At present, there is a variety of signal detecting method in mimo systems, as linearity test (ZF ZF detector, least mean-square error MMSE detector), non-linear detection (BLAST detector is divided into ZF-BLAST detector and MMSE-BLAST detector), maximum likelihood (ML) detect.

In linearity test, ZF ZF algorithm eliminates the interference between each antenna, but to amplify noise for cost, and least mean-square error MMSE algorithm has considered the interference of interference between antenna and noise, and make between data estimator and real data, to reach mean square error and minimize, its performance is better than ZF and detects.

Non-linear detection passes through repeatedly serial interference delete iteration, first rebuilds the highest transmitting antenna data of signal to noise ratio of making a start, and eliminates the impact of these data on reception antenna, and iteration repeatedly can obtain the data of all transmitting antennas afterwards.Nonlinear detector performance is better than linear detector, but needs the process of carrying out successive ignition and matrix inversion.

Maximum likelihood (ML) detects and searches for all possible originating data space at receiving terminal, and draws with Received signal strength apart from minimum value, in this, as estimation detected value.Maximum likelihood (ML) detection perform is excellent, but its complexity is very high, and exponentially increase with order of modulation and antenna configuration, and for the innovatory algorithm that maximum likelihood (ML) criterion proposes, as Sphere Decoding, complexity is still higher, and choosing of parameter is difficult to determine, brings certain difficulty to the application in real system.

Summary of the invention

(1) technical problem that will solve

The technical problem to be solved in the present invention is: how to provide a kind of MIMO detection method and device, with according to actual channel quality and communication system requirements situation flexible complexity and detection perform, realize the detection perform of varying level with the detection complexity of different brackets.

(2) technical scheme

For solving the problems of the technologies described above, the invention provides a kind of MIMO detection method, it comprises step:

A: r carries out linearity test to received signal, obtains corresponding the first estimated value sending signal

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

C: according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue not obtaining estimated value in described step B and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

D: merge the estimated value that described part sends signal the estimated value of signal is sent with described residue obtain corresponding the second estimated value sending signal

E: according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

Wherein, in described steps A, described first estimated value computing formula as follows:

${\hat{r}}_1=g\×r;$

Wherein, g is filtering matrix.

Wherein, the computing formula of described filtering matrix g is as follows:

G=(H ^hh) ^-1h ^h; Or,

g=（H ^HH+σ ²I） ^-1H ^H；

Wherein, H represents channel matrix, σ ²represent noise power.

Wherein, in described step B, according to predetermined iterations to received signal r to carry out the detailed process of non-linear detection as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\∉\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{\stackrel{\‾}{s}i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _iter; r _irepresent Received signal strength during i-th iteration, r ₁equal initial described Received signal strength r; G _irepresent filtering matrix, F (H) and represent calculation of filtered matrix G _ifunction, H represents channel matrix; (G _i) _jrepresent filtering matrix G _ijth row, s _irepresent filtering matrix G in i-th iteration _ithe row subscript of 2-Norm minimum in row vector; represent according to planisphere detection signal carry out hard decision, represent and send s in signal _ithe estimated value of individual symbol; represent the s of channel matrix H _ithat goes turns order; represent the s of signaling channel matrix H ₁, s ₂..., s _ibe classified as 0 matrix obtained.

Wherein, zero forcing algorithm or least-mean-square error algorithm calculation of filtered matrix G is adopted _i.

Wherein, described predetermined iterations is arranged according to the signal to noise ratio of communication system.

Wherein, described step C specifically comprises step:

C1: determine the probability of happening that often kind of variation mode is corresponding according to the signal to noise ratio of communication system;

C2: the estimated value sending signal according to described part the residue not obtained estimated value sends the location index of signal;

C3: according to the probability of happening that often kind of variation mode is corresponding, the transmission signal corresponding to described location index carries out bit inversion operation, obtains the estimated value that corresponding residue sends signal

Wherein, in described step e, the formula of Maximum Likelihood Detection is as follows:

$\hat{r}=\arg \underset{x\∈R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|;$

Wherein, H represents channel matrix; X is all possible vector in vector space R; represent the corresponding final estimated value sending signal.

The present invention also provides a kind of MIMO checkout gear, and described device comprises:

Linearity test unit, carries out linearity test for r to received signal, obtains corresponding the first estimated value sending signal

Non-linear detection unit, for according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

Variation estimate detecting unit, for according to probability of happening corresponding to often kind of variation mode, according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue not obtaining estimated value in described step B and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

Merge cells, sends the estimated value of signal for merging described part the estimated value of signal is sent with described residue obtain corresponding the second estimated value sending signal

Maximum Likelihood Detection unit, for according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

Wherein, described device also comprises:

Complexity control unit, for determining predetermined iterations according to the signal to noise ratio of communication system;

Variance control unit, for determining according to the signal to noise ratio of communication system the probability of happening that often kind of variation mode is corresponding.

(3) beneficial effect

MIMO detection method described in the embodiment of the present invention and device, can according to actual channel quality and communication system requirements situation flexible complexity and detection perform, realize the detection perform of varying level with the detection complexity of different brackets, be with a wide range of applications.

Accompanying drawing explanation

Fig. 1 is the structural representation of MIMO communication system;

Fig. 2 is MIMO detection method flow chart described in the embodiment of the present invention;

Fig. 3 is the modular structure schematic diagram of MIMO checkout gear described in the embodiment of the present invention.

Embodiment

Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples for illustration of the present invention, but are not used for limiting the scope of the invention.

For MIMO(multiple-input and multiple-output) communication system, need to carry out MIMO at receiving terminal and detect the transmission data obtaining transmitting terminal.The invention provides a kind of adjustable method realizing MIMO signal detection of complexity and device, can according to actual channel quality and system requirements situation flexible complexity and detection perform, and detect in conjunction with linear MIMO detection, non-linear partial MIMO, meristic variation is carried out to linear MIMO testing result, the detection perform of varying level is realized with the detection complexity of different brackets.

Fig. 1 is the structural representation of MIMO communication system, and as shown in Figure 1, described MIMO communication system, has N at transmitting terminal _troot antenna, receiving terminal has N _rroot antenna; Then Received signal strength meets following relation with transmission signal:

r=H×x+n；

Wherein, r is Received signal strength, and its dimension is N _r× 1, N _rfor reception antenna number. $r=[r_1^{\′},$ $r_2^{\′}...r_{N_r}^{\′}],$ R ' ₁, r ' ₂... be respectively the Received signal strength of every root reception antenna; X is for sending signal, and its dimension is N _t× 1, N _tfor transmitting antenna number.

x ₁, x ₂... be respectively the transmission signal of every root transmitting antenna; H represents channel matrix, and its dimension is N _r× N _t.N represents noise jamming, and its dimension is N _r× 1.

Fig. 2 is MIMO detection method flow chart described in the embodiment of the present invention, and as shown in Figure 2, described method comprises step:

A: r carries out linearity test to received signal, obtains corresponding the first estimated value sending signal

In step, receiving terminal to received signal r carries out linearity test, obtains the first estimated value to sending signal concrete formula is as follows:

${\hat{r}}_1=g\×r;$

Wherein, for N _t× 1 dimension, N _tfor transmitting antenna number, g is filtering matrix;

Wherein, can adopt in the present embodiment but be not limited to ZF (ZF) algorithm or least mean-square error (MMSE) algorithm calculates described filtering matrix g.

When adopting zero forcing algorithm, g=(H ^hh) ^-1h ^h;

When adopting least-mean-square error algorithm, g=(H ^hh+ σ ²i) ^-1h ^h.

Wherein, H is channel matrix, can be obtained, σ by channel estimating ²for noise power.

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

In stepb, according to the predetermined iterations of complexity control unit instruction, carry out non-linear detection to received signal, obtain estimated value part being sent to signal concrete grammar is as follows:

Complexity control unit determines the iterations N of non-linear detection _iter, and N _iter<N _t, wherein N _tfor transmitting antenna number.Complexity control unit regulates iterations N automatically according to communication system signal to noise ratio snr _iter.

Table one is N _t=N _r=4, when adopting 16QAM modulation, the iterations N that complexity control unit exports _iterwith the rule change relation table of signal to noise ratio snr.

Table 1 iterations N _iterwith the rule change relation table of signal to noise ratio snr

It should be noted that, in actual applications, iterations N _iterbe not limited to shown in table one with the relation of signal to noise ratio snr, those skilled in the art can according to flexibly adjustment form one data such as actual conditions and system configuration, to average out between detection complexity and detection perform.

At complexity control unit according to signal to noise ratio snr determination iterations N _iterafterwards, non-linear detection unit carries out N _itersecondary iterative detection.MIMO iterative detection process is specific as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\&NotElement;\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{\stackrel{\&OverBar;}{s}i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _iter; r _irepresent Received signal strength during i-th iteration, r ₁equal initial described Received signal strength r; G _irepresent filtering matrix, F (H) and represent calculation of filtered matrix G _ifunction, H represents channel matrix; (G _i) _jrepresent filtering matrix G _ijth row, s _irepresent filtering matrix G in i-th iteration _ithe row subscript of 2-Norm minimum in row vector; represent according to planisphere detection signal carry out hard decision, represent and send s in signal _ithe estimated value of individual symbol; represent the s of channel matrix H _ithat goes turns order; represent the s of signaling channel matrix H ₁, s ₂..., s _ibe classified as 0 matrix obtained.It should be noted that, the interference elimination order in above-mentioned algorithm sorts according to the energy of the generalized inverse matrix reception column vector signal of each iteration, ensures N under the control of complexity control unit like this _iterthe detected value of secondary iteration is local optimum.

Wherein, can adopt in the present embodiment but be not limited to ZF sequence interference cancellation algorithm or least mean-square error sequence interference cancellation algorithm carry out calculation of filtered matrix G _i.

Therefore, in stepb, the iterations N that non-linear detection unit will determine according to complexity control unit _iterexport estimated value part being sent to signal dimension be N _t× 1, but owing to not carrying out iterative detection completely, wherein only have N _iterindividual symbol has value, and all the other the unknowns are 0.

C: according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue not obtaining estimated value in described step B and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

In step C, iterative detection in step B is not estimated to the transmission signal obtained, by variance control unit controls, obtain according to the detection of steps A neutral line bit variation is carried out to respective symbol, thus produces the estimated value of corresponding receiving symbol concrete grammar is as follows:

For the signal using M contrast, its each constellation symbol has log ₂m bit number, possible variation kind has log ₂m kind.Such as 16QAM is modulated, each constellation symbol is made up of 4 bit binary code, then have the possibility of 4 kinds of variations: make a variation 1 bit ... make a variation 4 bits, variation is carries out negate (0 change 1 to the bit of corresponding position in this bit group, 1 becomes 0), variance control unit is for determining the probability of happening of often kind of variation when generating estimate symbol.The object of variance control unit is to make this sign estimation value to have may equal actual value greatlyr, is the local best practice of one.Variance control unit can regulate automatically according to communication system signal to noise ratio snr.

Table two is N _t=N _rduring=4,16QAM modulation, the probability of happening of often kind of variation mode that variance control unit exports and the relation of SNR.

The relation table of table 2 variation mode, probability of happening and SNR

It should be noted that, in actual applications, the probability of happening of often kind of variation mode that variance control unit exports and the relation of SNR are not limited to shown in table one, and those skilled in the art can according to adjustment form two data flexibly such as actual conditions and system configuration.

The part obtained in step B sends the estimated value of signal dimension be N _t× 1, owing to not carrying out iterative detection completely, wherein only have N _iterindividual symbol has value, and all the other positions are 0, obtains the location index index=[index that position is 0 signal ₁, index ₂index _n], wherein n=N _t-N _iter.Steps A carries out linearity test to received signal, obtains the first estimated value to all sending signal dimension be N _t× 1.According to the instruction of index vector index and variance control unit, right in the symbol corresponding with index vector index carry out bit inversion operation, generate new Vector Groups dimension be N _t× 1, wherein only have n=N _t-N _iterindividual symbol has value, and all the other are 0.

D: merge the estimated value that described part sends signal the estimated value of signal is sent with described residue obtain corresponding the second estimated value sending signal

In step D, to step B and step C testing result and merge. with be N _t× 1 dimensional vector, and in have N _iterindividual symbol has value, in have n=N _t-N _iterindividual symbol has value, and with middle symbol has the location index of value to be complementary relationship.Then right with merging, obtaining the second estimated value to sending signal dimension be N _t× 1.

E: according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

In step e, by steps A testing result with step D testing result form new vector space R, the dimension of new vector space R is N _t× 2.

The signal vector that search is nearest with Received signal strength r in vector space R, carries out maximum likelihood input, obtains final estimated value concrete formula is as follows:

$\hat{r}=\arg \underset{x\&Element;R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|$

Wherein, H is channel matrix, and r is Received signal strength, and x is all possible vector in vector space R, and in the present embodiment, the size of vector space R is n _tfor transmitting antenna number. be the final estimated value to sending signal.

Fig. 3 is the modular structure schematic diagram of MIMO checkout gear described in the embodiment of the present invention, and as shown in Figure 3, this MIMO checkout gear comprises:

Linearity test unit 100, carries out linearity test for r to received signal, obtains corresponding the first estimated value sending signal

Non-linear detection unit 200, for according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

Variation estimate detecting unit 300, for according to probability of happening corresponding to often kind of variation mode, according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue not obtaining estimated value in described step B and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

Merge cells 400, sends the estimated value of signal for merging described part the estimated value of signal is sent with described residue obtain corresponding the second estimated value sending signal

Maximum Likelihood Detection unit 500, for according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

Complexity control unit 600, for determining predetermined iterations according to the signal to noise ratio of communication system;

Variance control unit 700, for determining according to the signal to noise ratio of communication system the probability of happening that often kind of variation mode is corresponding.

MIMO detection method described in the embodiment of the present invention and device, can according to actual channel quality and communication system requirements situation flexible complexity and detection perform, realize the detection perform of varying level with the detection complexity of different brackets, be with a wide range of applications.

Above execution mode is only for illustration of the present invention; and be not limitation of the present invention; the those of ordinary skill of relevant technical field; without departing from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all equivalent technical schemes also belong to category of the present invention, and scope of patent protection of the present invention should be defined by the claims.

Claims (10)

1. a MIMO detection method, is characterized in that, comprises step:

A: r carries out linearity test to received signal, obtains corresponding the first estimated value sending signal

B: according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

C: according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue not obtaining estimated value in described step B and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

D: merge the estimated value that described part sends signal the estimated value of signal is sent with described residue obtain corresponding the second estimated value sending signal

E: according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

2. the method for claim 1, is characterized in that, in described steps A, and described first estimated value computing formula as follows:

${\hat{r}}_1=g\&times;r;$

Wherein, g is filtering matrix.

3. method as claimed in claim 2, it is characterized in that, the computing formula of described filtering matrix g is as follows:

G=(H ^hh) ^-1h ^h; Or,

g＝(H ^HH+σ ²I) ^-1H ^H；

Wherein, H represents channel matrix, σ ²represent noise power.

4. the method for claim 1, is characterized in that, in described step B, according to predetermined iterations to received signal r to carry out the detailed process of non-linear detection as follows:

Initialization: i=1, G ₁=F (H);

Iterative process:

$s_i=\arg \underset{j\&NotElement;\{s_1,s_2,...s_{i-1}\}}{\min }\left|\right|{\left(G_i\right)}_j\left|\right|;$

$W_{s_i}={\left(G_i\right)}_{s_i};$

$y_{s_i}=W_{s_i}{r}_i;$

${\hat{x}}_{s_i}=Q\left(y_{s_i}\right);$

$r_{i+1}=r_i-{\hat{x}}_{s_i}{\left(H\right)}_{s_i}^T;$

$G_{i+1}=F\left(H_{{\stackrel{\&OverBar;}{S}}_i}\right);$

i＝i+1；

Wherein, i is less than or equal to predetermined iterations N _iter; r _ireceived signal strength corresponding during expression i-th iteration, r ₁equal initial described Received signal strength r; G _irepresent filtering matrix, F (H) and represent the function of calculation of filtered matrix, H represents channel matrix; (G _i) _jrepresent filtering matrix G _ijth row, s _irepresent filtering matrix G in i-th iteration _ithe row subscript of 2-Norm minimum in row vector; represent according to planisphere detection signal carry out hard decision, represent and send s in signal _ithe estimated value of individual symbol; represent the s of channel matrix H _ithat goes turns order; represent the s of signaling channel matrix H ₁, s ₂..., s _ibe classified as 0 matrix obtained.

5. method as claimed in claim 4, is characterized in that, adopts zero forcing algorithm or least-mean-square error algorithm calculation of filtered matrix G _i.

6. method as claimed in claim 4, it is characterized in that, described predetermined iterations is arranged according to the signal to noise ratio of communication system.

7. the method for claim 1, is characterized in that, described step C specifically comprises step:

C1: determine the probability of happening that often kind of variation mode is corresponding according to the signal to noise ratio of communication system;

C2: the estimated value sending signal according to described part the residue not obtained estimated value sends the location index of signal;

C3: according to the probability of happening that often kind of variation mode is corresponding, the transmission signal corresponding to described location index carries out bit inversion operation, obtains the estimated value that corresponding residue sends signal

8. the method for claim 1, is characterized in that, in described step e, the formula of Maximum Likelihood Detection is as follows:

$\hat{r}=\arg \underset{x\&Element;R}{\min }\left|\right|r-\mathrm{Hx}\left|\right|;$

Wherein, H represents channel matrix; X is all possible vector in vector space R; represent the corresponding final estimated value sending signal.

9. a MIMO checkout gear, is characterized in that, described device comprises:

Linearity test unit, carries out linearity test for r to received signal, obtains corresponding the first estimated value sending signal

Non-linear detection unit, for according to predetermined iterations to received signal r carry out non-linear detection, obtain corresponding part and send the estimated value of signal

Variation estimate detecting unit, for according to probability of happening corresponding to often kind of variation mode, according to described first estimated value the estimated value of signal is sent with described part signal is sent to the residue of carrying out non-linear detection through described non-linear detection unit and do not obtain estimated value and carries out bit inversion operation, obtain the estimated value that corresponding residue sends signal

Merge cells, sends the estimated value of signal for merging described part the estimated value of signal is sent with described residue , obtain corresponding the second estimated value sending signal

Maximum Likelihood Detection unit, for according to described first estimated value with described second estimated value obtain vector space R, in described vector space R, r carries out Maximum Likelihood Detection to received signal, obtains the nearest signal vector of distance Received signal strength r sends signal final estimated value as correspondence

10. device as claimed in claim 9, it is characterized in that, described device also comprises:

Complexity control unit, for determining predetermined iterations according to the signal to noise ratio of communication system;

Variance control unit, for determining according to the signal to noise ratio of communication system the probability of happening that often kind of variation mode is corresponding.