CN107222246A - The efficient extensive MIMO detection method and system of a kind of approximated MMSE-based performance - Google Patents

The efficient extensive MIMO detection method and system of a kind of approximated MMSE-based performance Download PDF

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CN107222246A
CN107222246A CN201710392735.7A CN201710392735A CN107222246A CN 107222246 A CN107222246 A CN 107222246A CN 201710392735 A CN201710392735 A CN 201710392735A CN 107222246 A CN107222246 A CN 107222246A
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matrix
extensive mimo
vector
iteration
mmse
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CN107222246B (en
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张川
吴至榛
尤肖虎
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Southeast University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0256—Channel estimation using minimum mean square error criteria

Abstract

The invention discloses the efficient extensive MIMO detection method and system of a kind of approximated MMSE-based performance, by introducing preconditioning technique, the present invention can dramatically speed up the iterative rate of traditional GS methods, so that extensive MIMO detection algorithms proposed by the present invention still can quickly approach the performance of accurate MMSE detection algorithms in severe communication environments (channel that such as transmit/receive antenna number is close or spatial coherence is larger).Numerical simulation result shows that the bit error rate performance that extensive MIMO detection algorithms proposed by the present invention are shown in severe communication environments is better than based on Neumann series, GS methods, the extensive MIMO detection algorithms of the tradition of CG methods.On the other hand, cyclic shift characteristic of the GS iteration in element renewal process has been excavated, so that it can carry out GS iterative operations with relatively low hardware consumption and delay the system innovation that the present invention is provided.

Description

The efficient extensive MIMO detection method and system of a kind of approximated MMSE-based performance
Technical field
The invention belongs to computer communication and digital circuit field, it is related to a kind of the efficient extensive of approximated MMSE-based performance MIMO detection method and system.
Background technology
Extensive multiple-input and multiple-output (MIMO) be acknowledged as the 5th generation (5G) wireless communication system important technology it One.The technology provides higher spectrum efficiency, faster peak-data speed by being equipped with a large amount of antennas in base station and user terminal Rate and than traditional small-scale more preferable energy efficiency of mimo system.However, along with the substantial increase of number of antennas, advising greatly The complexity of Baseband algorithms is also being sharply increased in mould mimo system.Wherein, the optimal multi-user test method of up-link, example As maximum likelihood (ML) detection and maximum a posteriori (MAP) method will become to be difficult to bear (due to them in terms of the computation complexity Exponential complexity).Therefore, more feasible and efficient detector design has attracted a large amount of concerns.In recent years, researcher will Sight has turned to linearity test method, such as traditional ZF (ZF) and least mean-square error (MMSE), because they are big There is suboptimum to detect performance and the characteristic of low-complexity in scale mimo system.
It is worth noting that, for the MMSE detection methods in extensive mimo system, its main computation complexity exists In inverting for high level matrix.Assuming that M is single-antenna subscriber number, according to accurate matrix inversion technique, such as Cholesky Decomposition method, then computation complexity is O (M3).If this means during M high number, accurate MMSE detections will need huge Amount of calculation and hardware consumption.
In recent years, have domestic and international researcher propose in succession based on Gauss-Seidel (GS) method, Neumann grades Number, the extensive MIMO detection method of conjugate gradient (CG), obtain the performance close to MMSE algorithms.These methods are total to It is it is all traditional iterations and numerical simulation method with point, although reduce computation complexity to a certain extent, but for Severe communication environments (channel that such as transmit/receive antenna number is close or spatial coherence is larger), their performance It can not even be restrained declining.
The content of the invention
Goal of the invention：In view of the shortcomings of the prior art, the present invention proposes a kind of the efficient extensive of approximated MMSE-based performance MIMO detection method and system.
Technical scheme：A kind of efficient extensive MIMO detection method of approximated MMSE-based performance, comprises the following steps：
Step 1：Pretreatment；By channel matrix H and received signal vector y input detectors, matched filter output is obtained yMF=HHY and regularization Gram matrix Ws=G+NoIM, wherein Gram matrixes G=HHH, NoFor noise variance, IMUnit square is tieed up for M Battle array, ()HFor conjugate transposition operation；
Step 2：Normalized matrixAnd standardized vectorWherein D is W diagonal element Matrix so that coefficient matrix diagonal entry is 1；
Step 3：Fore condition；Construct precondition matrix P=S+IM, design factor matrixAnd constant vector Wherein S be one andRelevant matrix：
Step 4：The coefficient matrix exported according to step 3And constant vectorIt is x to set iteration initial solution(0)=0, and start iterative operation, export testing result；Pseudo-code of the algorithm is as follows：
After K wheel iteration, x(K)The estimated result of signal as to be detected.
The present invention also provides a kind of efficient extensive MIMO detecting systems of approximated MMSE-based performance, including：
Fore condition module, for completing pretreatment, channel matrix H and received signal vector y input detectors are obtained Y is exported with wave filterMF=HHY and regularization Gram matrix Ws=G+NoIM, wherein Gram matrixes G=HHH, NoFor noise variance, IM Unit matrix, () are tieed up for MHFor conjugate transposition operation；Then normalized matrixAnd standardized vectorWherein D is W diagonal element matrix so that coefficient matrix diagonal entry is 1；Finally construct precondition matrix P=S+IM, design factor matrixAnd constant vectorWherein S be one andRelevant matrix；
GS iteration modules, for the coefficient matrix for completing to be exported according to fore condition moduleAnd constant vectorIt is x to set iteration initial solution(0)=0, and operation is iterated, retrieval result is exported, pseudo-code of the algorithm is as follows：
After K wheel iteration, x(K)The estimated result of signal as to be detected.
Further, described fore condition module includes matrix multiplier, the 2 adder battle arrays that 6 systolic arrayses are constituted Arrange and 1 is sought reciprocal unit；Wherein, matched filter output y is calculated with 2 systolic arraysesMF=HHY and regularization Gram squares Battle array W=G+NoIM, the wherein processing unit of systolic arrays is basic complex multiplier accumulator；Calculated and marked with another 2 systolic arrayses Standardization matrixAnd standardized vectorWherein D-1Obtained by asking reciprocal unit to calculate, seek reciprocal unit Generated by look-up table, the processing unit of systolic arrays is still basic complex multiplier accumulator；With remaining 2 systolic arrayses Design factor matrixAnd constant vectorWherein precondition matrix P=S+IM。
Further, described GS iteration modules include M-1 complex multiplier, adder and register, and it carries out every One wheel GS iteration needs M clock cycle, and M is transmitting antenna number.
Operation principle：In view of extensive mimo system up-link MMSE detect in filtering matrix W be Hermitian just Determine battle array and leading diagonal is dominant, the GS alternative manners that the present invention is used necessarily are restrained after successive ignition.In severe communication environments In (channel that such as transmit/receive antenna number is close or spatial coherence is larger), the Preconditioning method that the present invention is used is certain The spectral radius of Iterative Matrix can be reduced, so as to reach the convergent effect of acceleration.
Beneficial effect：Compared with prior art, emphasis of the present invention is considered in severe communication environments (such as transmit/receive antenna The close or larger spatial coherence channels of number) in reach the detection of approximated MMSE-based performance such as how relatively low computation complexity Effect.The GS alternative manners handled by using fore condition, the present invention can be obtained under conditions of same iterations than passing Unite based on Neumann series, GS methods, CG methods the extensive more preferable bit error rate performance of MIMO detection algorithms, especially exist Under severe communication environments (channel that such as transmit/receive antenna number is close or spatial coherence is larger), and changed in less The Detection results of approximated MMSE-based performance are obtained after generation number.On the other hand, excavate the system innovation that the present invention is provided Cyclic shift characteristic of the GS iteration in element renewal process, so that it can be carried out with relatively low hardware consumption and delay GS iterative operations.In addition, this characteristic also causes the design of corresponding control circuit to become very easy.
Brief description of the drawings
Fig. 1 is the bit error rate comparison diagram (transmitting antenna using signal detecting method of the present invention and other traditional detection methods Number is 32, and reception antenna number is 128, when coefficient correlation is 0)；
Fig. 2 is the bit error rate comparison diagram (transmitting antenna using signal detecting method of the present invention and other traditional detection methods Number is 32, and reception antenna number is 128, when coefficient correlation is 0.3)；
Fig. 3 is the bit error rate comparison diagram (transmitting antenna using signal detecting method of the present invention and other traditional detection methods Number is 16, and reception antenna number is 128, when coefficient correlation is 0.3)；
Fig. 4 is the bit error rate comparison diagram (transmitting antenna using signal detection algorithm of the present invention and other traditional detection algorithms Number is 8, and reception antenna number is 128, when coefficient correlation is 0.3)；
Fig. 5 present system schematic diagrames；
Fig. 6 is GS iteration module schematic diagrames in present system；
Fig. 7 is GS iteration module sequential schedulings schematic diagram in present system (when system transmitting antenna number is 4).
Embodiment
Below in conjunction with accompanying drawing, the case study on implementation of the present invention is described in detail；
An extensive MIMO up-line system is set up in the present embodiment and carries out simulated operation.It is up in extensive MIMO In link, typically there are N ＞ ＞ M (antenna for base station number N is much larger than transmitting antenna number, i.e. number of users M).M first different user production Raw parallel transmission bit stream is encoded by channel coding respectively, is then mapped to constellation symbol, and take constellation set Close energy normalized.Allow x=[x1, x2, x3..., xM]TRepresent to contain the biography produced from M user respectively in signal vector, x Defeated symbol, is mapped using 64-QAM modes.H represents that dimension is N × M channel matrixes, therefore the reception signal at uplink base station end Vectorial y can be expressed as
Y=Hx+n
Wherein y dimension is that N × 1, n is the additive white noise vector that N × 1 is tieed up, and it is N that its element, which obeys zero-mean variance,o Gaussian Profile.Uplink multiuser signal detection task is exactly from receiver received vector y=[y1, y2, y3..., yN]T Estimation transmission signal code x.Assuming that H is, it is known that using least mean-square error (MMSE) linearity test theory, to transmission signal vectors Estimation be expressed as
The estimation procedure is equivalent to solve system of linear equations
Based on above-mentioned model, the embodiment of the present invention discloses a kind of efficient extensive MIMO detection sides of approximated MMSE-based performance Method, comprises the following steps：
Step 1：Pretreatment, by channel matrix H and received signal vector y input detectors, obtains matched filter output yMF=HHY and regularization Gram matrix Ws=G+NoIM, wherein Gram matrixes G=HHH, NoFor noise variance, IMUnit square is tieed up for M Battle array, ()HFor conjugate transposition operation；
Step 2：CalculateWithWherein D is W diagonal element matrix so that coefficient matrix pair Diagonal element is 1；
Step 3：Fore condition, construction precondition matrix P=S+IM, calculateWithWherein S be one and Relevant matrix：
Step 4：Exported according to step 3WithIt is x to set iteration initial solution(0)=0, and start iteration Operation, output estimation retrieval result；Pseudo-code of the algorithm is as follows：
After K wheel iteration, x(K)The estimated result of signal as to be detected.
It is 128 × 32 for antenna configuration (N × M), channel correlation coefficient is 0 (i.e. H-matrix element is i.i.d. distributions) Extensive mimo system, mapped using 64-QAM, the efficient extensive MIMO detection algorithms of described approximated MMSE-based performance Numerical Simulation Results are shown in Fig. 1；It is 0.3 for channel correlation coefficient, antenna configuration is respectively 128 × 32,128 × 16,128 × 8 Extensive mimo system, the Numerical Simulation Results of the algorithm are shown in Fig. 2, Fig. 3 and Fig. 4.Wherein, NS, which is represented, is based on Neumann The detection algorithm of series, CG represents the detection algorithm based on conjugate gradient, and GS represents the detection algorithm based on traditional GS, PGS generations The efficient extensive MIMO detection algorithms of table approximated MMSE-based performance of the present invention, Cholesky represents accurate MMSE detections Algorithm.With the increase of spatial coherence it can be seen from Fig. 1 and Fig. 2 result, all algorithms contrasted are in equal iteration Bit error rate performance all have lost much under number of times, but the advantage that algorithm of the present invention compares other algorithms becomes brighter It is aobvious.It can be seen from Fig. 2, Fig. 3 and Fig. 4 when reception antenna quantity is 128, with the increasing of transmitting antenna number (number of users) Greatly, all algorithm bit error rate performances contrasted are gradually reduced, and required iterations is gradually increasing, but of the present invention Algorithm performance be still better than other several algorithms, and the error code of accurate MMSE detection algorithms can be approached after less iteration Rate performance.
As shown in figure 5, a kind of approximated MMSE-based performance used in hardware structure aspect, the present embodiment is efficient extensive MIMO detecting systems mainly include being fore condition module diagram in dotted line in fore condition module and GS iteration modules, figure.
Specifically, in the fore condition module, calculating process is as follows：
1) as shown in figure 5, (being labeled as in Figure 5 with 2 systolic arrayses) calculate matched filter output yMF=HHY and Regularization Gram matrix Ws=G+NoIM, wherein adder array is expressed asThe processing unit (PE) of systolic arrays is basic Complex multiplier accumulator (MAC), it is to be noted that the systolic arrays of calculating matrix-matrix multiplication is by M2Individual PE compositions, for calculating The systolic arrays of Matrix-Vector multiplication is made up of M PE；
2) (it is labeled as in Figure 5 with 2 systolic arrayses) normalized matrixAnd standardized vectorWherein D-1Obtain (asking reciprocal unit to be given birth to by look-up table by asking reciprocal unit (in Figure 5 labeled as inv) to calculate Into systolic arrays is made up of 2M real multipliers)；
3) (it is labeled as in Figure 5 with 2 systolic arrayses) design factor matrixAnd constant vectorIts Middle precondition matrix P=S+IMElement can be obtained directly from 2) middle, it is to be noted that the systolic arrays of calculating matrix-matrix multiplication By M2Individual PE compositions, the systolic arrays for calculating matrix-vector multiplication is made up of M PE.
As shown in fig. 6, in the GS iteration modules, calculating process is as follows：
1) in each clock cycle, the output of GS iteration modulesIts Middle complex multiplier and complex adder are respectively labeled as in figure 6WithDelay cell is labeled as D.By M clock week After phase, GS iteration (sequential scheduling as shown in fig. 7, D) in solid square corresponding diagram 6 is completed, the preceding M-1 clock cycle counts Calculate result to preserve in a register, notice that the b and A of each multiplier input value substitute also with clock cycle property；
2) after KM clock cycle, the estimated result of signal to be detected is obtained from register, wherein K is setting GS iterationses, as shown in fig. 7, element updates schematic diagram in M=4 system.
The present invention is by introducing fore condition (preconditioning) technology, and the present invention can dramatically speed up traditional GS side The iterative rate of method, so that extensive MIMO detection algorithms proposed by the present invention are in (such as transmitting/the reception of severe communication environments The channel that antenna number is close or spatial coherence is larger) in still can quickly approach the performance of accurate MMSE detection algorithms. Numerical simulation result shows, the bit error rate that extensive MIMO detection algorithms proposed by the present invention are shown in severe communication environments Performance is better than based on Neumann series, GS methods, the extensive MIMO detection algorithms of the tradition of CG methods.In addition, the present invention is carried Low hardware consumption and the circuit design of low latency are supplied.

Claims (4)

1. the efficient extensive MIMO detection method of a kind of approximated MMSE-based performance, it is characterised in that comprise the following steps：
Step 1：Pretreatment；By channel matrix H and received signal vector y input detectors, matched filter output y is obtainedMF= HHY and regularization Gram matrix Ws=G+NoIM, wherein Gram matrixes G=HHH, NoFor noise variance, IMUnit matrix is tieed up for M, (.)HFor conjugate transposition operation；
Step 2：Normalized matrixAnd standardized vectorWherein D is W diagonal element matrix, So that coefficient matrix diagonal entry is 1；
Step 3：Fore condition；Construct precondition matrix P=S+IM, design factor matrixAnd constant vectorWherein S be one andRelevant matrix：
Step 4：The coefficient matrix exported according to step 3And constant vectorIt is x to set iteration initial solution(0)= 0, and start iterative operation, export testing result；Pseudo-code of the algorithm is as follows：
After K wheel iteration, x(K)The estimated result of signal as to be detected.
2. a kind of efficient extensive MIMO detecting systems of approximated MMSE-based performance, it is characterised in that including：
Fore condition module, for completing pretreatment, by channel matrix H and received signal vector y input detectors, obtains matching filter Ripple device exports yMF=HHY and regularization Gram matrix Ws=G+NoIM, wherein Gram matrixes G=HHH, NoFor noise variance, IMFor M Tie up unit matrix, ()HFor conjugate transposition operation；Then normalized matrixAnd standardized vectorWherein D is W diagonal element matrix so that coefficient matrix diagonal entry is 1；Finally construct precondition matrix P=S+IM, design factor matrixAnd constant vectorWherein S be one andRelevant matrix；
GS iteration modules, for the coefficient matrix for completing to be exported according to fore condition moduleAnd constant vectorSet Iteration initial solution is x(0)=0, and operation is iterated, retrieval result is exported, pseudo-code of the algorithm is as follows：
After K wheel iteration, x(K)The estimated result of signal as to be detected.
3. a kind of efficient extensive MIMO detecting systems of approximated MMSE-based performance according to claim 2, it is characterised in that Matrix multiplier of the described fore condition module including 6 systolic arrayses compositions, 2 adder arrays and 1 ask reciprocal single Member；Wherein, matched filter output y is calculated with 2 systolic arraysesMF=HHY and regularization Gram matrix Ws=G+NoIM, its middle arteries The processing unit of dynamic array is basic complex multiplier accumulator；With another 2 systolic arrayses normalized matrix And standardized vectorWherein D-1Obtained by asking reciprocal unit to calculate, ask reciprocal unit to be generated by look-up table, pulsed The processing unit of array is still basic complex multiplier accumulator；With remaining 2 systolic arrayses design factor matrixAnd constant vectorWherein precondition matrix P=S+IM。
4. a kind of efficient extensive MIMO detecting systems of approximated MMSE-based performance according to claim 2, it is characterised in that Characterized in that, described GS iteration modules include M-1 complex multiplier, adder and register, it carries out each round GS Iteration needs M clock cycle, and M is transmitting antenna number.
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