CN104734756A - MIMO system detection method and device - Google Patents

Abstract

The invention is applicable to the field of communication and provides an MIMO system detection method and device. The method comprises the steps that an estimated value of channel interference plus noise power of an MIMO system is acquired; a symbol vector table of constellation points is obtained according to a constellation diagram of modulating signals; difference values of the squares of adjacent Euclidean distance values in the transmitted signals are searched for in the symbol vector table to be compared with the estimated value of the interference plus noise power, and survival symbols of the transmitted signals are obtained when predetermined comparison conditions are met; the posterior probability of each path is obtained through calculation according to the survival symbols of the transmitted signals and corresponding branch metrics. The choice of the survival symbols can be subjected to adaptive adjustment according to the interference plus noise power, and more survival symbols can be chosen under a low signal-to-noise ratio so that the bit error rate is smaller; chosen survival symbols can be reduced under a high signal-to-noise ratio, and the corresponding calculation amount is greatly reduced.

Description

A kind of mimo system detection method and device

Technical field

The invention belongs to the communications field, especially relate to a kind of mimo system and detect and method and apparatus.

Background technology

Multiple-input and multiple-output (MIMO) system is a core technology applying to 802.11n, its key concept effectively promotes the spectrum efficiency of wireless communication system by the spatial degrees of freedom utilizing many transmit antennas and many reception antennas and provided, and improves communication quality with promoting transmission rate.Because mimo system can, when not needing the data throughout (throughput) and the transmission range that increase system when increasing bandwidth or total transmitted power consume (transmit power expenditure) significantly, make this technology in getting most of the attention in recent years.

Multiple-input and multiple-output (MIMO) technology is that future mobile communication system realizes high data rate, high power system capacity and improves the important channel of transmission quality.MIMO technique and OFDM (OFDM) combine the MIMO-OFDM technology formed and are acknowledged as the wireless communication technology having development potentiality most, occupy very important status in LTE system.By Maximum Likelihood Detection decoding (MLD), mimo system can realize comparatively dominance energy.But the complexity that MLD detects can increase with exponential form along with the increase of number of antennas, and this makes the complexity of receiver greatly increase, and especially becomes difficult to achieve when antenna number is more.The practical application of MIMO technology in LTE system to be promoted further, design that complexity is low and the detection algorithm that performance is good is particularly important.

The detection method of current proposition, such as based on the maximum likelihood algorithm of tree search, or based on the adaptively selected survivor symbols algorithm of signal order, although the complexity of compute euclidian distances can be reduced when selecting survivor symbols, but the quantity of the survivor symbols in each stage only depends on primary sign, can not adaptive channel situation.

Summary of the invention

A kind of mimo system is the object of the present invention is to provide to detect and method and apparatus, to solve the detection method that prior art proposes, although the complexity of compute euclidian distances can be reduced when selecting survivor symbols, but the quantity of the survivor symbols in each stage only depends on carrier wave and primary sign, can not the problem of adaptive channel situation.

The present invention is achieved in that a kind of mimo system detection method, and described method comprises:

Obtain the interference plus noise power estimated value of the channel of mimo system;

According to the planisphere of modulation signal, calculate the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtain the symbolic vector table of constellation point;

According to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining;

According to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.

Another object of the present invention is to provide a kind of mimo system checkout gear, described device comprises:

Interference plus noise power estimated value acquiring unit, for obtaining the interference plus noise power estimated value of the channel of mimo system;

Symbolic vector table generation unit, for the planisphere according to modulation signal, calculates the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtains the symbolic vector table of constellation point;

Survivor symbols generation unit, for search according to described symbolic vector table the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining;

Posterior probability computing unit, for the accumulation branch metric of the survivor symbols that transmits described in basis and correspondence, calculates the posterior probability of every paths.

In the present invention, by calculating the symbolic vector table obtaining interference plus noise power estimated value and constellation point, according to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, obtain the survivor symbols transmitted, and according to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.The selection of survivor symbols of the present invention according to interference plus noise power Automatic adjusument, under low signal-to-noise ratio, can be selected more survivor symbols, thus make the error rate less; Under high s/n ratio, the survivor symbols of selection can reduce, and corresponding amount of calculation reduces greatly.

Accompanying drawing explanation

Fig. 1 is the realization flow figure of the mimo system detection method that the embodiment of the present invention provides;

Fig. 2 is that the data that the embodiment of the present invention provides carry out pretreated realization flow figure;

Fig. 3 is the realization flow figure of the interference plus noise power estimated value of the channel of the acquisition mimo system that the embodiment of the present invention provides;

Fig. 4 is the constellation segmentation schematic diagram that the embodiment of the present invention provides;

Fig. 5 is the realization flow figure searching first stage lucky symbol that the embodiment of the present invention provides;

The algorithm of the present invention that Fig. 6 provides for the embodiment of the present invention and the performance of BER comparison diagram of other already present algorithm under same computation complexity condition;

Fig. 7 is the structural representation of the mimo system checkout gear that the embodiment of the present invention provides.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.

The object of the embodiment of the present invention to be to solve in prior art when reducing the survivor symbols selected, due to the MIMO detection method proposed in prior art, maximum likelihood lattice such as based on globular decoding is searched for, or search for based on the tree of QRM algorithm, QRM algorithm can realize the performance being similar to maximum-likelihood decoding, but weak point is, algorithm time delay is comparatively large, and computational complexity is still higher.A kind of adaptive control algorithm based on maximum reliability proposed in the prior art, its object is to reduce the quantity at the survivor symbols of every one-phase.But, the object of these algorithms above-mentioned be all in order to reduce select survivor symbols time compute euclidian distances complexity, but the quantity of every one-phase survivor symbols only depends on carrier wave and primary sign, can not adaptive channel situation.

For solving the problem, the invention provides a kind of mimo system detection method, described method comprises: the interference plus noise power estimated value obtaining the channel of mimo system; According to the planisphere of modulation signal, calculate the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtain the symbolic vector table of constellation point; According to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining; According to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.

The present invention obtains the symbolic vector table of interference plus noise power estimated value and constellation point by calculating, according to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, obtain the survivor symbols transmitted, and according to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.The selection of survivor symbols of the present invention according to interference plus noise power Automatic adjusument, under low signal-to-noise ratio, can be selected more survivor symbols, thus make the error rate less; Under high s/n ratio, the survivor symbols of selection can reduce, and corresponding amount of calculation reduces greatly.Illustrate below in conjunction with accompanying drawing.

Fig. 1 shows the realization flow of the mimo system detection method that the embodiment of the present invention provides, and details are as follows:

In step S101, obtain the interference plus noise power estimated value of the channel of mimo system.

Before the survivor symbols step transmitted described in obtaining in step S102, described method also can comprise carries out pretreated step to data, specifically comprises step as shown in Figure 2:

In step s 201, at transmitting terminal, signal transmission is rearranged according to Signal to Interference plus Noise Ratio, obtains the channel matrix after resetting: wherein index (p) be expressed as p road reset after subscript.

In step S202, the channel matrix after described rearrangement is carried out QR decomposition and obtain wherein Q is N _r× N _tthe unitary matrice of dimension, R is N _t× N _tthe upper triangular matrix of dimension, and: $R=Q^H\hat{H}=\left[\begin{array}{cccc}{r}_{\mathrm{1,1}}& r_{\mathrm{1,2}}& ...& r_{1,N_t}\\ 0& r_{\mathrm{2,2}}& ...& r_{{2,N}_t}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& ...& r_{N_t-1,N_t-1}& r_{N_t-1,N_t}\\ 0& ...& 0& r_{N_t,N_t}\end{array}\right],$ Wherein N _rfor the number of reception antenna, N _tfor the number of transmitting antenna.

In step S203, at receiving terminal, by Q ^hbe multiplied with Received signal strength y, obtain quadrature receiving signal z,

$z\stackrel{\mathrm{\Δ}}{=}\left[\begin{array}{c}{z}_{N_t}\\ z_{N_t-1}\\ .\\ .\\ .\\ z_1\end{array}\right]=Q^{H}y=R\left[\begin{array}{c}{d}_{\mathrm{index}\left(H_t\right)}\\ d_{\mathrm{index}(N_t-1)}\\ .\\ .\\ .\\ d_{\mathrm{index}\left(1\right)}\end{array}\right]+\left[\begin{array}{c}{n}_1^{\′}\\ n_2^{\′}\\ .\\ .\\ .\\ n_{N_t}^{\′}\end{array}\right],$ D _pbe the transmission signal of p transmitting antenna, for

Concrete, the interference plus noise power estimated value step of the channel of described acquisition mimo system comprises following steps as shown in Figure 3:

In step S301, select the i-th row w of Walsh matrix _ias the pilot tone s of i-th transmitting antenna _i=w _is, wherein s is raw information, 1≤i≤N _t, N _tfor number of transmit antennas;

In step s 302, the i-th ' (1≤i '≤N of identical Walsh matrix is used _t) row to received signal $r_j={\mathrm{\Σ}}_{i=1}^P{h}_{j,i}{s}_i+n_j$ Carry out despreading can obtain: $\underset{n=1}{\overset{P}{\mathrm{\Σ}}}{r}_{j,n}{s}_{i^{\′},n}={\mathrm{Ph}}_{j,i^{\′}}+n_j^{\′},$ Channel parameter can estimate from P the training sequence intercoupled to obtain: ${\hat{h}}_{u,v}=(1/P){\mathrm{\Σ}}_{n=1}^P{r}_{j,n}{s}_{i^{\′},n}=h_{j,i^{\′}}+(n_j^{\′}/P),$ Wherein: P is the subcarrier number in each data packet frame shared by frequency pilot sign, s _{i '}=w _{i '}s, h _j,ifor channel coefficients, n _jfor the noise of a jth reception antenna, h _{j, i '}for h _j,ichannel coefficients corresponding after despreading conversion, n ' _jfor n _jnoise corresponding after despreading conversion, u is transmitting antenna sequence number, and v is reception antenna sequence number, r _j,nfor the signal on the n-th subcarrier that a jth reception antenna receives, s _{i ', n}for the i-th ' row of local Walsh matrix is to the signal after the n-th subcarrier despreading.

In step S303, according to described pilot tone, by formula: ${\mathrm{\σ}}^2=\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\left|{\hat{h}}_{u,v}\right|}^2-{\left|\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\hat{h}}_{u,v}\right|}^2$ Calculate the interference plus noise power estimated value of the channel of described mimo system, wherein: σ ²for interference plus noise power, N _rfor the number of reception antenna.

In step s 102, according to the planisphere of modulation signal, calculate the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtain the symbolic vector table of constellation point.

Concrete, example is modulated to QPSK, as shown in Figure 4, planisphere is divided into 16 squares, each foursquare coordinate is each foursquare center, for each square, all symbols on constellation are carried out ascending order arrangement according to the Euclidean distance of self and foursquare central point, and we can obtain the form of 16 × 16.

Namely the number of path candidate is number of constellation points M, order quadrant detection method is utilized to determine z ' ₁fall into position.Quadrant can utilize z ' ₁real part and imaginary part determine, such as real part is just, imaginary part is that timing is just at first quartile; Real part is just, just at the second quadrant when imaginary part is for bearing.Mobile x-axis and y-axis, ensure that center is consistent with the quadrant of selection.Repeat 3 identical localization process, certain square is by as z ' ₁position.According to detected foursquare index, lookup table Τ, obtains a symbolic vector { c arranged ₁=c _1,1, c _1,2..., c _{1, M}.

In step s 103, according to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining.

Concrete, described according to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols step transmitted described in obtaining comprises searches first stage lucky symbol S ₁symbol S lucky for the m stage _m(2≤m≤N _t) step, wherein:

Search first stage lucky symbol S ₁step comprise step as shown in Figure 5:

In step S501, order z ' is searched according to quadrant method ₁affiliated foursquare position, the symbolic vector { c of the correspondence that transmits according to affiliated foursquare location lookup first ₁=c _1,1, c _1,2..., c _{1, M}, wherein z ₁for the data message of the quadrature receiving signal z correspondence position 1 in step S203;

In step S502, according to formula calculate i-th Euclidean distance square;

In step S503, if E _{1, i}-E _{1, i-1}>=α σ ², α is the constant preset, σ ²for the interference plus noise power estimated in 2, vector { c ₁=c _1,1, c _1,2..., c _{1, i-1}be selected as survivor symbols, and S ₁=i-1, otherwise, make i=i+1, repeat step S502 and S503, until judge E _{1, i+1}-E _{1, i}>=α σ ²till establishment, obtain the survivor symbols of first stage.

Search m stage lucky symbol S _mstep comprise:

Obtain m-1 stage each survivor branch c _{m-1, k}(1≤k≤S _m-1) and carry out ascending order arrangement;

The survivor symbols S in m stage is selected by iterative method _m.

Concrete, each survivor branch c of described acquisition m-1 stage _{m-1, k}(1≤k≤S _m-1) and carry out ascending order alignment step and comprise: order $z_m^{\′}=\{z_m-[r_{N_t-m+1,N_t-m+2},r_{N_t-m+1,N_t-m+3},...,r_{N_t-m+1,N_t}\left]c_{m-1,k}\right\}/r_{N_t-m+1,N_t-m+1},$ Z ' is searched according to quadrant method _maffiliated foursquare position, according to affiliated foursquare location lookup m the corresponding each survivor branch c that transmits _{m-1, k}(1≤k≤S _m-1) and carry out ascending order arrangement, wherein: z _mfor the data message of quadrature receiving signal z correspondence position m in calculating process, z ' _mfor the amended data message of quadrature receiving signal z correspondence position m in calculating process.

The described survivor symbols S being selected the m stage by iterative method _mstep comprises:

S1, according to formula ${\hat{E}}_{m,x}={|z_m-[r_{N_t-m+1,N_t-m+1},r_{N_t-m+1,N_t-m+2},...,r_{N_t-m+1,N_t}\left]{\hat{c}}_{m,x}^T\right|}^2+E_{m-1,x}$ Calculate accumulation branch metric, wherein z _mfor the data message of quadrature receiving signal z correspondence position m in calculating process, 1≤x≤S _m-1, be N _t-m+1 reception antenna receives N _tthe Received signal strength of-m+1 transmitting antenna, for;

S2, calculates select as a jth survival candidate symbol in m stage, corresponding accumulation branch metric is wherein for making accumulation branch metric as x in its domain of definition value when getting maximum corresponding to x;

S3, if E _m,j-E _{m, 1}be less than or equal to α σ ², then make j=j+1, and judge whether be greater than predetermined value, if be greater than predetermined value, then make and return step S2, if be less than or equal to predetermined value, then make s _m=j, calculates then make s _m=j, calculates and return step S2.

Concrete, for the m stage, suppose that (m-1) stage survivor branch is corresponding branch metric is to each branch c _{m-1, k}(1≤k≤S _m-1), testing process is as follows:

5a) from z _min deduct c _{m-1, k}, can obtain:

$z_{m^{\′}}=\{z_m-[r_{N_t-m+1,N_t-m+2},r_{N_t-m+1,N_t-m+3},...,r_{N_t-m+1,N_t}\left]c_{m-1,k}\right\}/r_{N_t-m+1,N_t-m+1};$

5b) based on the quadrant detection method identical with (4), obtain m 16 candidate symbol sets transmitted, it is for branch c _{m-1, k}it is ascending order arrangement;

5c) when obtaining all branch c _{m-1, k}(1≤k≤S _m-1) ascending order arrangement after, use iterative algorithm, select the survivor symbols S in m stage _m.Concrete iterative step is as follows:

The first step, initialization: order t ^*=φ, j=1.

Second step, for 1≤x≤S _m-1, order calculate accumulation branch metric:

${\hat{E}}_{m,x}={|z_m-[r_{N_t-m+1,N_t-m+1},r_{N_t-m+1,N_t-m+2},...,r_{N_t-m+1,N_t}\left]{\hat{c}}_{m,x}^T\right|}^2+E_{m-1,x};$

3rd step, calculates select as a jth survival candidate symbol in m stage, corresponding accumulation branch metric is

4th step, judges E _m,j-E _{m, 1}whether be less than or equal to α σ ², if so, then jump to the 5th step, otherwise finishing iteration;

5th step, order judge whether be greater than 16, if so, then make and jump to the 3rd step, otherwise jump to the 6th step;

6th step, order s _m=j, calculates then the 3rd step is jumped to.

In step S104, according to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.

The accumulation branch metric of the survivor symbols transmitted described in described basis and correspondence, the posterior probability step calculating every paths is specially:

Select individual individual path, corresponding accumulation branch metric is the posterior probability of each passes through formula: calculate, wherein e _{min, p, b, q}be expressed as under, p paths b position is the minimum accumulation branch metric of q

Concrete, select individual individual path, corresponding accumulation branch metric is the posterior probability of each calculates by following formula:

${\mathrm{\Λ}}_{p,b}=\sqrt{e_{\min .p,b,-1}}-\sqrt{e_{\min ,p,b,1}}$

Wherein e _{min, p, b, q}be expressed as under, p paths b position is the minimum accumulation branch metric of q for the present invention, consider the situation some only having-1 or 1, be now difficult to the log-likelihood ratio directly calculating them, we adopt following steps to calculate:

6a) for all elements in survivor symbols Candidate Set, calculate square e of the minimum Eustachian distance of every _{min, p, b, q}

6b) for the situation those being-1 and 1, the minimum Eustachian distance obtained in a first step square in select a larger value, the Euclidean distance now selected square be the mean value of these symbols, Euclidean distance square be exist for the situation those being-1 and 1.

6c) mean value in 5b is multiplied by a default factor-beta to carry out follow-up calculating, described factor-beta obtains suitable empirical value by emulation.

Fig. 6 is algorithm of the present invention and the performance of BER comparison diagram of other already present algorithm under same computation complexity condition, simulated conditions is as shown in Figure 6: mimo system has transmitting antenna and reception antenna number to be 4, modulation system is 16QAM, supposes that time synchronized and channel estimating are desirable completely.

Algorithm of the present invention and some already present schemes compare by we on BER and complexity.Such as adaptive control QRM-MLD algorithm, adaptively selected QRM-MLD algorithm and ZF (ZF) algorithm.

As can be seen from Fig. 6 we, algorithm of the present invention is better than existing MIMO detection algorithm performance.In addition, the present invention is when close bit error rate value performance, and complexity of the present invention reduces greatly.

Fig. 7 shows the structural representation of mimo system checkout gear provided by the invention, and as shown in Figure 7, mimo system checkout gear of the present invention comprises:

Interference plus noise power estimated value acquiring unit 701, for obtaining the interference plus noise power estimated value of the channel of mimo system;

Symbolic vector table generation unit 702, for the planisphere according to modulation signal, calculates the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtains the symbolic vector table of constellation point;

Survivor symbols generation unit 703, for search according to described symbolic vector table the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining;

Posterior probability computing unit 704, for the accumulation branch metric of the survivor symbols that transmits described in basis and correspondence, calculates the posterior probability of every paths.

Preferably, described interference plus noise power estimated value acquiring unit comprises:

Chooser unit, for selecting the i-th row w of Walsh matrix _ias the pilot tone s of i-th transmitting antenna _i=w _is, wherein s is raw information, 1≤i≤N _t, N _tfor number of transmit antennas;

Despreading subelement, for using the i-th ' (1≤i '≤N of identical Walsh matrix _t) row to received signal $r_j={\mathrm{\Σ}}_{i=1}^P{h}_{j,i}{s}_i+n_j$ Carry out despreading can obtain: $\underset{n=1}{\overset{P}{\mathrm{\Σ}}}{r}_{j,n}{s}_{i^{\′},n}={\mathrm{Ph}}_{j,i^{\′}}+n_j^{\′},$ Channel parameter is: ${\hat{h}}_{u,v}=(1/P){\mathrm{\Σ}}_{n=1}^P{r}_{j,n}{s}_{i^{\′},n}=h_{j,i^{\′}}+(n_j^{\′}/P);$

Wherein: P is the subcarrier number in each data packet frame shared by frequency pilot sign, s _{i '}=w _{i '}s, h _j,ifor channel coefficients, n _jfor the noise of a jth reception antenna, h _{j, i '}for h _j,ichannel coefficients corresponding after despreading conversion, n ' _jfor n _jnoise corresponding after despreading conversion, u is transmitting antenna sequence number, and v is reception antenna sequence number, r _j,nfor, s _{i ', n}for;

Interference plus noise power estimated value computation subunit, for according to described pilot tone, by formula: ${\mathrm{\σ}}^2=\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\left|{\hat{h}}_{u,v}\right|}^2-{\left|\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\hat{h}}_{u,v}\right|}^2$ Calculate the interference plus noise power estimated value of the channel of described mimo system, wherein: σ ²for interference plus noise power, N _rfor the number of reception antenna.

Preferably, described device also comprises:

Rearrangement units, for being rearranged according to Signal to Interference plus Noise Ratio by signal transmission, obtains the channel matrix after resetting: wherein index (p) be expressed as p road reset after subscript;

Resolving cell, obtains for the channel matrix after described rearrangement being carried out QR decomposition wherein Q is N _r× N _tthe unitary matrice of dimension, R is N _t× N _tthe upper triangular matrix of dimension, and: $R=Q^H\hat{H}=\left[\begin{array}{cccc}{r}_{\mathrm{1,1}}& r_{\mathrm{1,2}}& ...& r_{1,N_t}\\ 0& r_{\mathrm{2,2}}& ...& r_{{2,N}_t}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& ...& r_{N_t-1,N_t-1}& r_{N_t-1,N_t}\\ 0& ...& 0& r_{N_t,N_t}\end{array}\right],$ Wherein N _rfor the number of reception antenna, N _tfor the number of transmitting antenna;

Quadrature receiving signature computation unit, at receiving terminal, by Q ^hbe multiplied with Received signal strength y, obtain quadrature receiving signal z,

$z\stackrel{\mathrm{\Δ}}{=}\left[\begin{array}{c}{z}_{N_t}\\ z_{N_t-1}\\ .\\ .\\ .\\ z_1\end{array}\right]=Q^{H}y=R\left[\begin{array}{c}{d}_{\mathrm{index}\left(H_t\right)}\\ d_{\mathrm{index}(N_t-1)}\\ .\\ .\\ .\\ d_{\mathrm{index}\left(1\right)}\end{array}\right]+\left[\begin{array}{c}{n}_1^{\′}\\ n_2^{\′}\\ .\\ .\\ .\\ n_{N_t}^{\′}\end{array}\right],$ D _pbe the transmission signal of p transmitting antenna, for

The checkout gear of mimo system shown in Fig. 6 is corresponding with method described in Fig. 1 to Fig. 5, does not repeat at this.

In several embodiment provided by the present invention, should be understood that, disclosed apparatus and method, can realize by another way.Such as, device embodiment described above is only schematic, such as, the division of described unit, be only a kind of logic function to divide, actual can have other dividing mode when realizing, such as multiple unit or assembly can in conjunction with or another system can be integrated into, or some features can be ignored, or do not perform.Another point, shown or discussed coupling each other or direct-coupling or communication connection can be by some interfaces, and the indirect coupling of device or unit or communication connection can be electrical, machinery or other form.

The described unit illustrated as separating component or can may not be and physically separates, and the parts as unit display can be or may not be physical location, namely can be positioned at a place, or also can be distributed in multiple network element.Some or all of unit wherein can be selected according to the actual needs to realize the object of the present embodiment scheme.

In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, also can be that the independent physics of unit exists, also can two or more unit in a unit integrated.Above-mentioned integrated unit both can adopt the form of hardware to realize, and the form of SFU software functional unit also can be adopted to realize.

If described integrated unit using the form of SFU software functional unit realize and as independently production marketing or use time, can be stored in a computer read/write memory medium.Based on such understanding, the part that technical scheme of the present invention contributes to prior art in essence in other words or all or part of of this technical scheme can embody with the form of software product, this computer software product is stored in a storage medium, comprising some instructions in order to make a computer equipment (can be personal computer, server, or the network equipment etc.) perform all or part of of method described in each embodiment of the present invention.And aforesaid storage medium comprises: USB flash disk, portable hard drive, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. various can be program code stored medium.

The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.

Claims (10)

1. a mimo system detection method, is characterized in that, described method comprises:

Obtain the interference plus noise power estimated value of the channel of mimo system;

According to the planisphere of modulation signal, calculate the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtain the symbolic vector table of constellation point;

According to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining;

According to the accumulation branch metric of the described survivor symbols that transmits and correspondence, calculate the posterior probability of every paths.

2. method according to claim 1, it is characterized in that, the interference plus noise power estimated value step of the channel of described acquisition mimo system is specially:

Select the i-th row w of Walsh matrix _ias the pilot tone s of i-th transmitting antenna _i=w _is, wherein s is raw information, 1≤i≤N _t, N _tfor number of transmit antennas;

Use the i-th ' (1≤i '≤N of identical Walsh matrix _t) row to received signal carry out despreading can obtain: $\underset{n=1}{\overset{P}{\mathrm{\Σ}}}{r}_{j,n}{s}_{i^{\′},n}={\mathrm{Ph}}_{j,i^{\′}}+n_j^{\′},$ Channel parameter is:

${\hat{h}}_{u,v}=(1/P){\mathrm{\Σ}}_{n=1}^P{r}_{j,n}{s}_{i^{\′},n}=h_{j,i^{\′}}+(n_j^{\′}/P),$ Wherein: P is the subcarrier number in each data packet frame shared by frequency pilot sign, s _{i '}=w _{i '}s, h _j,ifor channel coefficients, n _jfor the noise of a jth reception antenna, r _jfor the Received signal strength of a jth reception antenna, h _{j, i '}for h _j,ichannel coefficients corresponding after despreading conversion, n ' _jfor n _jnoise corresponding after despreading conversion, u is transmitting antenna sequence number, and v is reception antenna sequence number, r _j,nfor the signal on the n-th subcarrier that a jth reception antenna receives, s _{i ', n}for the i-th ' row of local Walsh matrix is to the signal after the n-th subcarrier despreading;

According to described pilot tone, by formula: ${\mathrm{\σ}}^2=\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\left|{\hat{h}}_{u,v}\right|}^2-{\left|\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\hat{h}}_{u,v}\right|}^2$ Calculate the estimated value of the channel disturbance plus noise power of described mimo system, wherein: σ ²for interference plus noise power estimated value, N _rfor the number of reception antenna.

3. method according to claim 1, it is characterized in that, described to search according to described symbolic vector table the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, before the survivor symbols step transmitted described in obtaining, described method also comprises:

Signal transmission is rearranged according to Signal to Interference plus Noise Ratio, obtains the channel matrix after resetting: wherein index (p) be expressed as p road reset after subscript;

Channel matrix after described rearrangement is carried out QR decomposition to obtain wherein Q is N _r× N _tthe unitary matrice of dimension, R is N _t× N _tthe upper triangular matrix of dimension, and: $R=Q^H\hat{H}=\left[\begin{array}{cccc}{r}_{\mathrm{1,1}}& r_{\mathrm{1,2}}& ...& r_{1,N_t}\\ 0& r_{\mathrm{2,2}}& ...& r_{2,N_t}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& ...& r_{N_t-1,N_t-1}& r_{N_t-1,N_t}\\ 0& ...& 0& r_{N_t,N_t}\end{array}\right],$ Wherein N _rfor the number of reception antenna, N _tfor the number of transmitting antenna;

At receiving terminal, by Q ^hbe multiplied with Received signal strength y, obtain quadrature receiving signal z,

$z\stackrel{\mathrm{\Δ}}{=}\left[\begin{array}{c}{z}_{N_t}\\ z_{N_t-1}\\ .\\ .\\ .\\ z_1\end{array}\right]=Q^{H}y=R\left[\begin{array}{c}{d}_{\mathrm{index}\left(N_t\right)}\\ d_{\mathrm{index}(N_t-1)}\\ .\\ .\\ .\\ d_{\mathrm{index}\left(1\right)}\end{array}\right]+\left[\begin{array}{c}{n}_1^{\′}\\ n_2^{\′}\\ .\\ .\\ .\\ n_{N_t}^{\′}\end{array}\right],$ D _pbe the transmission signal of p transmitting antenna, for

4. method according to claim 3, it is characterized in that, described according to described symbolic vector table search the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols step transmitted described in obtaining comprises searches first stage lucky symbol S ₁symbol S lucky for the m stage _m(2≤m≤N _t) step, wherein:

Search first stage lucky symbol S ₁step comprise:

Order z ' is searched according to quadrant method ₁affiliated foursquare position, the symbolic vector { c of the correspondence that transmits according to affiliated foursquare location lookup first ₁=c _1,1, c _1,2..., c _{1, M}, wherein z ₁for the data message of described quadrature receiving signal z correspondence position 1;

According to formula calculate i-th Euclidean distance square;

If E _{1, i}-E _{1, i-1}>=α σ ², α is the constant preset, σ ²for the interference plus noise power estimated in 2, vector { c ₁=c _1,1, c _1,2..., c _{1, i-1}be selected as survivor symbols, and S ₁=i-1, otherwise judge E _{1, i+1}-E _{1, i}>=α σ ², until meet the demands;

Search m stage lucky symbol S _mstep comprise:

Obtain m-1 stage each survivor branch c _{m-1, k}(1≤k≤S _m-1) and carry out ascending order arrangement;

The survivor symbols S in m stage is selected by iterative method _m.

5. method according to claim 4, is characterized in that, each survivor branch c of described acquisition m-1 stage _{m-1, k}(1≤k≤S _m-1) and carry out ascending order alignment step and comprise:

Order $z_m^{\′}=\{z_m-[r_{N_t-m+1,N_t-m+2},r_{N_t-m+1,N_t-m+3},...,r_{N_t-m+1,N_t}\left]c_{m-1,k}\right\}/r_{N_t-m+1,N_t-m+1},$ Z ' is searched according to quadrant method _maffiliated foursquare position, according to affiliated foursquare location lookup m the corresponding each survivor branch c that transmits _{m-1, k}(1≤k≤S _m-1) and carry out ascending order arrangement, wherein: z _mfor the data message of quadrature receiving signal z correspondence position m in calculating process, z ' _mfor the amended data message of quadrature receiving signal z correspondence position m in calculating process.

6. method according to claim 4, be is characterized in that, the described survivor symbols S being selected the m stage by iterative method _mstep comprises:

S1, according to formula ${\hat{E}}_{m,x}={|z_m-[r_{N_t-m+1,N_t-m+1},r_{N_t-m+1,N_t-m+2},...,r_{N_t-m+1,N_t}\left]{\hat{c}}_{m,x}^T\right|}^2+E_{m-1,x}$ Calculate accumulation branch metric, wherein z _mfor the data message of quadrature receiving signal z correspondence position m in calculating process, 1≤x≤S _m-1, be N _t-m+1 reception antenna receives N _tthe Received signal strength of-m+1 transmitting antenna, it is an xth survivor branch in m stage;

S2, calculates select as a jth survival candidate symbol in m stage, corresponding accumulation branch metric is wherein for making accumulation branch metric as x in its domain of definition value when getting maximum corresponding to x;

S3, if E _m,j-E _{m, 1}be less than or equal to α σ ², then make j=j+1, and judge whether be greater than predetermined value, if be greater than predetermined value, then make and return step S2, if be less than or equal to predetermined value, then make s _m=j, calculates then make s _m=j, calculates and return step S2.

7. method according to claim 1, it is characterized in that, the accumulation branch metric of the survivor symbols transmitted described in described basis and correspondence, the posterior probability step calculating every paths is specially:

Select individual individual path, corresponding accumulation branch metric is the posterior probability of each passes through formula: calculate, wherein e _{min, p, b, q}be expressed as under, p paths b position is the minimum accumulation branch metric of q

8. a mimo system checkout gear, is characterized in that, described device comprises:

Interference plus noise power estimated value acquiring unit, for obtaining the interference plus noise power estimated value of the channel of mimo system;

Symbolic vector table generation unit, for the planisphere according to modulation signal, calculates the Euclidean distance of each foursquare central point in all constellation point and described planisphere on planisphere and ascending order arranges, obtains the symbolic vector table of constellation point;

Survivor symbols generation unit, for search according to described symbolic vector table the adjacent Euclidean distance value in transmitting square difference compare with described interference plus noise power estimated value, when meeting predetermined comparison condition, the survivor symbols transmitted described in obtaining;

Posterior probability computing unit, for the accumulation branch metric of the survivor symbols that transmits described in basis and correspondence, calculates the posterior probability of every paths.

9. device according to claim 8, it is characterized in that, described interference plus noise power estimated value acquiring unit comprises:

Chooser unit, for selecting the i-th row w of Walsh matrix _ias the pilot tone s of i-th transmitting antenna _i=w _is, wherein s is raw information, 1≤i≤N _t, N _tfor number of transmit antennas;

Despreading subelement, for using the i-th ' (1≤i '≤N of identical Walsh matrix _t) row to received signal $r_j={\mathrm{\Σ}}_{i=1}^P{h}_{j,i}{s}_i+n_j$ Carry out despreading can obtain: $\underset{n=1}{\overset{P}{\mathrm{\Σ}}}{r}_{j,n}{s}_{i^{\′}n}={\mathrm{Ph}}_{j,i^{\′}}+n_j^{\′},$ Channel parameter is:

${\hat{h}}_{u,v}=(1/P){\mathrm{\Σ}}_{n=1}^P{r}_{j,n}{s}_{i^{\′},n}=h_{j,i^{\′}}+(n_j^{\′}/P),$

Wherein: P is the subcarrier number in each data packet frame shared by frequency pilot sign, s _{i '}=w _{i '}s, h _j,ifor channel coefficients, n _jfor the noise of a jth reception antenna, h _{j, i '}for h _j,ichannel coefficients corresponding after despreading conversion, n ' _jfor n _jnoise corresponding after despreading conversion, u is transmitting antenna sequence number, and v is reception antenna sequence number, r _j,nfor, s _{i ', n}for;

Interference plus noise power estimated value computation subunit, for according to described pilot tone, by formula:

${\mathrm{\σ}}^2=\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\left|{\hat{h}}_{u,v}\right|}^2-{\left|\frac{P^2}{N_t{N}_r}\underset{u=1}{\overset{N_t}{\mathrm{\Σ}}}\underset{v=1}{\overset{N_r}{\mathrm{\Σ}}}{\hat{h}}_{u,v}\right|}^2$ Calculate the interference plus noise power estimated value of the channel of described mimo system, wherein: σ ²for interference plus noise power, N _rfor the number of reception antenna.

10. device according to claim 8, it is characterized in that, described device also comprises:

Rearrangement units, for being rearranged according to Signal to Interference plus Noise Ratio by signal transmission, obtains the channel matrix after resetting: wherein index (p) be expressed as p road reset after subscript;

Resolving cell, obtains for the channel matrix after described rearrangement being carried out QR decomposition wherein Q is N _r× N _tthe unitary matrice of dimension, R is N _t× N _tthe upper triangular matrix of dimension, and: $R=Q^H\hat{H}=\left[\begin{array}{cccc}{r}_{\mathrm{1,1}}& r_{\mathrm{1,2}}& ...& r_{1,N_t}\\ 0& r_{\mathrm{2,2}}& ...& r_{2,N_t}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& ...& r_{N_t-1,N_t-1}& r_{N_t-1,N_t}\\ 0& ...& 0& r_{N_t,N_t}\end{array}\right],$ Wherein N _rfor the number of reception antenna, N _tfor the number of transmitting antenna;

Quadrature receiving signature computation unit, at receiving terminal, by Q ^hbe multiplied with Received signal strength y, obtain quadrature receiving signal z,

$z\stackrel{\mathrm{\Δ}}{=}\left[\begin{array}{c}{z}_{N_t}\\ z_{N_t-1}\\ .\\ .\\ .\\ z_1\end{array}\right]=Q^{H}y=R\left[\begin{array}{c}{d}_{\mathrm{index}\left(N_t\right)}\\ d_{\mathrm{index}(N_t-1)}\\ .\\ .\\ .\\ d_{\mathrm{index}\left(1\right)}\end{array}\right]+\left[\begin{array}{c}{n}_1^{\′}\\ n_2^{\′}\\ .\\ .\\ .\\ n_{N_t}^{\′}\end{array}\right],$ D _pbe the transmission signal of p transmitting antenna, for