CN101582742B - Method for detecting iteration of multiple input multiple output (MIMO) system, system thereof and device thereof - Google Patents
Method for detecting iteration of multiple input multiple output (MIMO) system, system thereof and device thereof Download PDFInfo
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Abstract
The invention discloses a method for detecting the iteration of a multiple input multiple output (MIMO) system, a system thereof and a device thereof. The method comprises the following steps of: wheninitializing an iteration process, adopting a soft in soft out parallel soft interference cancellation MMSESIC MIMO detecting method with a signal which is received by a receiver and a channel fading matrix which is estimated by the channel; when continuing the iteration process, taking the sum of residual interference and noise which are deleted by the parallel soft interference as an equivalent noise with the signal which is received by the receiver, bit priori information which is outputted by a channel encoder in the former iteration and a channel fading matrix which is estimated by the c hannel, wherein, the each component of the equivalent noise is similar to be mutually independent gaussian random variables, and executing a soft in soft out MMSESIC MIMO detecting computation under the model; and hard deciding code bit posterior information which is outputted by the soft in soft out channel encoder, executing a CRC check, outputting the hard decision result of the information source code bit posterior information, and taking the result as the final result of interative detection.
Description
Technical Field
The present invention relates to the field of wireless communication systems, and in particular, to a method, a system, and a device for iterative detection of a mimo system.
Background
With the rapid increase of the number of wireless communication users and the rapid development of broadband multimedia services, higher and higher requirements are put on the transmission rate and performance of wireless communication systems. Nowadays, the spectrum resources are increasingly tense, and a Multiple Input Multiple Output (MIMO) technology is attracting attention because it can greatly improve the transmission quality and spectrum efficiency of a wireless communication system. Current research suggests that iterative receivers are an effective way to approach MIMO channel capacity for MIMO systems. In an iterative receiver, the MIMO detector should implement soft-in soft-out. A Soft Input Soft Output (SISO) MIMO detector with the best error rate performance is a Maximum Likelihood (ML) detector, but the complexity increases exponentially with the number of antennas and the size of a modulation constellation, and thus cannot be applied practically. Therefore, high performance and low complexity MIMO detection algorithms are becoming important in iterative receiver research.
Currently, in research for iterative receivers, Serial Interference Cancellation (SIC) MIMO detection algorithms based on Minimum Mean Square Error (MMSE) are widely used. However, the soft-in and soft-out mmsisci MIMO detection involves complex matrix inversion operation and still has high complexity. To further reduce complexity, Takumi ITO, Xiaoodong Wang, Yoshikazu Kakura et al, in Performance composition of MF and MMSE combined iterative Power manager and V-BLAST technical in MIMO/OFDM systems, VTC 2003-Fall, October 2003, (1): 488-492, it is proposed to use soft-in soft-out MMSE SIC MIMO detection in the initial iteration process, and soft-in soft-out matched Filter (MF, Match Filter) SIC MIMO detection in the subsequent iteration process. The number of transmitting and receiving antennas is Nr，NtIn the MIMO system, the complexity of the iterative receiver is increased from O (N) under the premise of less loss of bit error rate performancer 3Nt) Reduce to O (N)r 2Nt). However, this scheme does not take into account that the MIMO detector can cancel the interference between the multiple antennas well, and therefore, in fact, the subsequent iteration stages still achieve less performance gain with higher complexity.
Disclosure of Invention
In view of this, the present invention provides an iterative detection method, system and device for a mimo system, which reduces the processing complexity of the iterative detection on the premise that the iterative detection performance is not significantly reduced.
Based on the above object, the present invention provides an iterative detection method for a MIMO system, which includes:
A. during initial iterative processing, a soft-in soft-out minimum mean square error serial interference cancellation multi-in multi-out MMSE SIC MIMO detection method is adopted by utilizing a signal received by a receiver and a channel fading matrix obtained by channel estimation;
B. during subsequent iteration processing, signals received by a receiver, bit prior information output by a channel decoder in last iteration and a channel fading matrix obtained by channel estimation are utilized, the sum of residual interference and noise after parallel soft interference deletion is used as equivalent noise, each component of the equivalent noise is approximate to a Gaussian random variable which is independent mutually, and soft-in soft-out minimum mean square error parallel soft interference deletion multi-in multi-out MMSE PSIC MIMO detection calculation is carried out under the model;
C. b, hard judgment is carried out on the posterior information of the coded bits output by the soft-in soft-out channel decoder, CRC (cyclic redundancy check) is carried out, and if the coded blocks are not correct and the number of iterations is smaller than the total number of iterations N, the step B is returned; otherwise, entering the step D;
D. and after the iterative detection is finished, outputting a hard decision result of the information source bit posterior information as a final result of the iterative detection.
Optionally, one iteration processing procedure in the method includes: the soft-in soft-out MIMO detector calculates the external information of the coded bits by using the signals received by the receiver, the channel fading matrix obtained by channel estimation and the prior information output by the channel decoder in the last iteration processing, and the external information becomes the input prior information of the soft-in soft-out channel decoder after passing through a de-interleaver. And the channel decoder calculates the obtained coded bit external information according to the prior information and the code structure, and the coded bit external information is used as the prior information after passing through the interleaver for the next iteration processing of the iteration receiving.
Optionally, in the first iteration of the method, the prior information output by the channel decoder in the last iteration processing is 0.
Optionally, in the subsequent iteration processing of the method, the calculation of the weighting vector in the soft-in soft-out MMSE psicm detection calculation process does not include matrix inversion.
Optionally, the soft-in and soft-out MMSE PSIC MIMO detection calculation process in the method includes the following steps:
calculating the mean value E(s) of all symbols to be detected according to the bit prior information output by the soft-in and soft-out channel decoder in the last iterationi) Sum variance var(s)i)，(i＝1，2，L，Ni) (ii) a According to E(s)i) After the receiving end is processed by PSIC, the symbol S is obtained by calculating the signal r received by the receiver and the channel fading matrix H obtained by channel estimationkEquivalent single-transmitting multi-receiving signal rkThe following were used:
calculating a signal skIs estimated value of Wherein The ith element is calculated by the following formula (2):
wherein, <math>
<mrow>
<msubsup>
<mi>σ</mi>
<msup>
<mi>n</mi>
<mi>k</mi>
</msup>
<mn>2</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mo>[</mo>
<munderover>
<mi>Σ</mi>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>N</mi>
<mi>t</mi>
</msub>
</munderover>
<mrow>
<mo>(</mo>
<msup>
<mrow>
<mo>|</mo>
<msub>
<mi>h</mi>
<mi>ij</mi>
</msub>
<mo>|</mo>
</mrow>
<mn>2</mn>
</msup>
<mi>var</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mi>j</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msubsup>
<mi>σ</mi>
<mi>n</mi>
<mn>2</mn>
</msubsup>
<mo>]</mo>
<mo>-</mo>
<msup>
<mrow>
<mo>|</mo>
<msub>
<mi>h</mi>
<mi>ik</mi>
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<mn>2</mn>
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<mi>var</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>s</mi>
<mi>k</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
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<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
</math>
the mapping into symbols S is calculated according to the formulas (4) and (5)kOf the coded bits λ1[bj k]：
μS-MMSE(k)＝wkhk
Wherein, <math>
<mrow>
<msubsup>
<mi>σ</mi>
<mrow>
<mi>S</mi>
<mo>-</mo>
<mi>MMSE</mi>
</mrow>
<mn>2</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
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<mo>=</mo>
<msub>
<mi>μ</mi>
<mrow>
<mi>S</mi>
<mo>-</mo>
<mi>MMSE</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msup>
<mrow>
<mo>[</mo>
<msub>
<mi>μ</mi>
<mrow>
<mi>S</mi>
<mo>-</mo>
<mi>MMSE</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mi>k</mi>
<mo>)</mo>
</mrow>
<mo>]</mo>
</mrow>
<mn>2</mn>
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<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
</math>
optionally, the method said symbol SkEquivalent single-transmitting multi-receiving signal rkIn the calculation of (1), a symbol soft estimate value E(s)i) Obtained by the following process:
bit prior information lambda output by soft-in soft-out channel decoder2[bπ(i)]Calculating a soft estimate E(s) of the symbol according to the principle of averagingi) The estimated value is used as prior information of MMSE PSICMI detection:
optionally, in the method, the variance of the symbol soft estimate in formula (3) is obtained by the following process:
using a priori information lambda2[bπ(i)]According to the principle of averaging, a soft estimate of the sign modulo square is calculated:
and calculating the variance of the symbol soft estimation value according to a variance calculation formula by using the symbol soft estimation value and the symbol modulus squared soft estimation value obtained by calculation of the formulas (8) and (9):
var(si)＝E(|si|2)-E(si)2(i＝1，2，…，Nt) (10)
optionally, the total iteration number of the method is a preset fixed value, or is adaptively determined according to a certain criterion in the iteration process.
Based on the above object, the present invention further provides an iterative detection system for MIMO system, comprising: the MIMO soft-in and soft-out detection method comprises a receiving antenna, a channel estimator, a soft-in and soft-out MIMO detector, a de-interleaver, a soft-in and soft-out channel decoder and an interleaver, wherein the detection of the soft-in and soft-out MIMO detector adopts the iterative detection method.
Based on the above object, the present invention further provides an iterative detection device for MIMO system, which is disposed in a soft-in and soft-out MIMO detector of a MIMO system receiver, and employs the iterative detection method.
From the above, it can be seen that the present invention provides an iterative detection method, system and device for low-complexity MIMO system based on MMSE, for the first MIMO systemThe secondary iteration processing adopts a Soft-in Soft-out MMSE SIC MIMO detection algorithm to obtain the extrinsic information of the coded bit, the subsequent iteration processing adopts a Soft-in Soft-out simplified MMSE PSIC (Parallel Soft Interference cancellation) MIMO detection algorithm to obtain the extrinsic information of the coded bit, and the actual iteration processing times of the iterative receiver are jointly determined through a CRC (cyclic redundancy check) result and the total iteration times N. Therefore, the processing complexity of the iterative detection method can be greatly reduced on the premise that the iterative detection performance is not remarkably reduced. As can be seen from simulation analysis, the overall performance of the system is not remarkably reduced by applying the method, and the complexity is O (N)r 3Nt) Reduce to O (N)rNt). Moreover, the invention has simple application, small change to the existing system and better compatibility with the existing system.
Drawings
Fig. 1 is a schematic structural diagram of a transmitting end of a MIMO system in the prior art;
fig. 2 is a schematic structural diagram of a MIMO receiving system according to an embodiment of the present invention;
FIG. 3 is a schematic flowchart of an MMSE-based iterative detection method for a low-complexity MIMO system according to an embodiment of the present invention;
fig. 4 is a diagram illustrating comparison between the performance of a conventional iterative detection algorithm and that of the iterative detection algorithm of the present invention in a specific example.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
Referring to fig. 1, the MIMO system transmitter includes: a source generator 101, a channel encoder 102, an interleaver 103, a modulator 104, a serial-to-parallel converter 105, and a transmit antenna 106.
Source { a } generated by the source generator 101iSymbol sequence s is generated after coding by a channel coder 102, bit interleaving by an interleaver 103 and modulation by a modulator 104iIs a sequence of symbols siIs converted into a plurality of signal streams [ s ] by a serial-to-parallel converter 1051，s2，...，sNt]And transmitted by the transmit antenna 106.
Referring to fig. 2, the MIMO system receiver includes: a receive antenna 201, a channel estimator 202, a soft-in soft-out MIMO detector 203, a deinterleaver 204, a soft-in soft-out (SISO) channel decoder 205, and an interleaver 206.
The multiple signal streams sent by the transmitter of the MIMO system pass through the MIMO channel and are received by the multiple receiving antennas 201 of the receiver, and any iteration processing procedure includes: soft-in soft-out MIMO detector 203 utilizes signals received by receive antenna 201
(where r is Hs + n, where H is a MIMO channel fading matrix and n is white gaussian noise) as a function of the transmitter transmit signal s, and the bit prior information λ obtained by the SISO channel decoder 205 through the bit interleaver 204 in the last iteration process2[bπ(i)](in the first iteration, this information is 0) and the channel estimator 202 calculates the extrinsic information λ of the coded bits by the soft-in and soft-out MIMO detector 203 for the channel fading matrix H obtained by channel estimation1[bπ(i)]The extrinsic information is bit deinterleaved by deinterleaver 204 to generate λ1[bi]As input a priori information to SISO channel decoder 205. SISO channel decoder 205 calculates the obtained coded bit-wise information lambda from the a priori information and the coding structure2[bi]Is bit interleaved by interleaver 206 to generate λ2[bπ(i)]And the prior information is used for the next iteration processing of the iterative receiver.
The invention provides an MMSE-based low-complexity MIMO system iterative detection method, which specifically comprises the following steps:
step 1: and (5) performing initial iteration processing.
The method comprises the steps of calculating external information of coded bits by utilizing a signal r received by a receiver and a channel fading matrix H obtained by channel estimation and adopting a soft-in soft-out MMSE SIC MIMO detection method, wherein the external information becomes input prior information lambda of a soft-in soft-out channel decoder after passing through a de-interleaver1[bi]. And the SISO channel decoder calculates the obtained coded bit external information according to the prior information and the code structure, and the coded bit external information is used as the prior information after passing through the interleaver for the next iteration processing of the iterative receiver.
Step 2: and (5) subsequent iteration processing.
Using the signal r received by the receiver and the bit prior information lambda output by the channel decoder in the last iteration2[bπ(i)]And a channel fading matrix H obtained by channel estimation, and the iterative processing of MMSE PSIC MIMO detection is simplified by adopting soft-in and soft-out.
The simplified iterative processing of MMSE PSIC MIMO detection in this embodiment mainly includes: and taking the sum of the residual interference and the noise after the parallel soft interference is deleted as equivalent noise, wherein each component of the equivalent noise is approximate to a Gaussian random variable which is independent from each other, and performing soft-in and soft-out MMSE PSIC MIMO detection calculation under the model. Wherein the calculation of the weighting vector may not include matrix inversion.
For the transmitted signal skThe detection specifically comprises the following steps:
according to the bit prior information lambda output by the soft-in soft-out channel decoder in the last iteration2[bπ(i)]Calculating the mean value E(s) of all symbols to be detectedi) Sum variance var(s)i)，(i＝1，2，L，Nt) Then according to E(s)i) R and H are calculated to obtain a symbol s after the receiving end is processed by PSICkIs a Single Input Multiple Output (SIMO) receiving signal rk。
Calculating the signal SkIs estimated value of Where w is the weight vector of the MMSE filtering, the ith element is calculated by the following formula (2) (3):
wherein | andi＊Representing complex conjugate, σn 2Representing the noise variance, h, of the receiverijWhich represents the elements located in the ith row and jth column of the channel matrix H.
Based on the obtained symbol estimation value
Calculating the symbol prior probability according to equations (4) and (5)
μS-MMSE(k)＝wkhk
Wherein h iskRepresenting the kth column of the channel matrix H. According to prior information Computing the mapping into symbols SkOf the coded bits of (a) is determined by the outer logarithmic likelihood ratio lambda of the coded bits1[bj k](i.e., extrinsic information).
The outer information output by the MIMO detection is used as the prior information of the soft-in and soft-out channel decoder after being de-interleaved. And the channel decoder calculates the posterior information and the external information of the coded bits according to the prior information and the code structure, wherein the external information is used as the prior information of the soft-in and soft-out MIMO detector in the next iteration processing after passing through the interleaver.
And step 3: and (5) judging iteration stop.
And carrying out hard decision on the posterior information of the coded bits output by the SISO channel decoder, and carrying out CRC (cyclic redundancy check). If the CRC checks that the coding block is incorrect and the number of iterations performed is less than the total number of iterations N, returning to the step 2; otherwise, go to step 4. The total iteration number N may be a preset fixed number, or may be adaptively determined according to a certain criterion during the iteration process.
And 4, step 4: and finishing the iterative detection.
And outputting a hard judgment result of the information source bit posterior information as a final result of the iterative detection. And finishing the iterative detection.
The solution according to the invention is described in further detail below in a specific example, in which the parameter settings do not affect the generality.
Setting the number of transmitting and receiving antennas N in the systemr＝N t4, the Turbo code generator polynomial, the inner interleaving and puncturing method refer to 3GPP specification 3GPP TS 25.222, Multiplexing and channel coding (TDD), 2004, the code block length is 5112, the code rate is 1/2, the SISO decoder adopts MAX-LOG-MAP algorithm, the decoding iteration number is 8, QPSK modulation, the preset maximum iteration number N is 4, the channel is a flat uncorrelated Rayleigh channel, and is an ideal channel estimation.
As shown in FIG. 1, the source bits { a }iCoded, interleaved and 2MGenerating symbol sequence s after M-QAM modulation of orderi}，{siAre divided into N by serial-to-parallel conversiontThe channel signal stream is transmitted by the transmitting antenna, passes through the MIMO channel H, and is received by the receiving end NrAnd receiving by the receiving antenna. Neglecting the time parameter, setting the signal vector sent by the transmitting antenna as MIMO channel matrix <math>
<mrow>
<mi>H</mi>
<mo>=</mo>
<msub>
<mrow>
<mo>(</mo>
<msub>
<mi>h</mi>
<mi>ik</mi>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<msub>
<mi>N</mi>
<mi>r</mi>
</msub>
<mo>×</mo>
<msub>
<mi>N</mi>
<mi>t</mi>
</msub>
</mrow>
</msub>
<mo>,</mo>
</mrow>
</math> The received signal vector is then expressed as:
referring to fig. 3, the steps of applying the embodiment of the iterative detection method for the MMSE-based low-complexity MIMO system according to the present invention are as follows:
1) using a priori information lambda2[bπ(i)]Calculating a soft estimate E(s) of the symbol according to the principle of averagingi) The estimated value is used as prior information of MMSE PSIC MIMO detection:
wherein, Bm jIs a constellation point SjM-th bit of (1), Sj∈ΩS，ΩSIs a set of modulation constellation points.
2) Using a priori information lambda2[bπ(i)]According to the principle of averaging, a soft estimate of the sign modulo square is calculated:
3) and calculating the variance of the symbol soft estimation value according to a variance calculation formula by using the symbol soft estimation value and the symbol modulus squared soft estimation value obtained by calculation of the formulas (8) and (9):
var(si)＝E(|si|2)-E(si)2(i＝1，2，…，Nt) (10)
4) symbol soft estimate value E(s) calculated using equation (8)i) And carrying out parallel soft interference deletion on the received signal r:
calculating a variance of equivalent noise approximated by a sum of residual interference and white gaussian noise using a variance of the symbol soft estimate calculated by equation (10):
calculating each element w of MMSE weighting vector by using the equivalent noise variance calculated by the formula (3) and the channel matrix H1 k，w2 k，...，
Estimating the transmission symbol by using the MMSE weighting vector calculated by the formula (2) and the interference-cancelled received signal obtained by the formula (1):
the mean and variance of the symbol estimates obtained by equation (11) are calculated.
μS-MMSE(k)＝wkhk
Calculating the mean value and the variance of the symbol estimation value calculated according to the formula (5), and calculating the extrinsic information lambda of each bit mapped into the symbol by combining the characteristic that the output of MMSE filtering accords with Gaussian distribution1[bj k]。
Wherein, bj kIs a symbol SkJ-th bit of (S)l∈ΩS，Sj +，Sj -Respectively represent constellation points with j bits of +1 and-1, and Bm lIs a constellation point SlThe mth bit of (1). Lambda [ alpha ]1[bj k]And detecting the output extrinsic information for MIMO. The outer information sequence is de-interleaved and then used as the prior information of the SISO channel decoder. And the SISO channel decoder calculates the posterior information and the external information of the coded bits according to the prior information and the code structure, wherein the external information is used as the prior information of the MIMO detector in the next iteration processing after passing through the interleaver.
And step 303, judging iteration stop, carrying out hard judgment on the posterior information of the coded bits output by the SISO channel decoder, and carrying out CRC (cyclic redundancy check). If the CRC checks that the coding block is incorrect and the number of iterations performed is less than the total number of iterations N equal to 4, return to step 302; otherwise, the CRC checks that the coding block is correct, or the number of iterations performed is greater than or equal to 4, and the process proceeds to step 304.
And step 304, finishing the iterative detection, and outputting a hard decision result of the information source bit posterior information as a final result of the iterative detection. And finishing the iterative detection.
As can be deduced from the above calculation steps, the complexity of the simplified MMSE PSIC MIMO detection algorithm is O (N)rNt) Order of magnitude, while the complexity of conventional MMSE PSIC MIMO detection will reach O (N)r 3Nt) In order to achieve the above object, the iterative detection method for the low-complexity MIMO system based on MMSE provided by the present invention greatly reduces the computational complexity of iterative reception.
Fig. 4 is a simulation result of the method of the present invention, wherein the dotted line is the result of the 4 th iteration of the method of the present invention, and compared with the conventional iterative detection method, the performance of the low complexity MIMO system iterative detection method based on MMSE of the present invention is not significantly reduced.
The above-described embodiments are merely exemplary embodiments of the present invention, which should not be construed as limiting the invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A multiple input multiple output MIMO system iterative detection method is characterized in that,
A. during initial iterative processing, utilizing a signal received by a receiver and a channel fading matrix obtained by channel estimation, and adopting a soft-in soft-out minimum mean square error serial interference cancellation multi-in multi-out MMSE SIC MIMO detection method to calculate external information of a coded bit, wherein the external information becomes input prior information of a soft-in soft-out channel decoder through a de-interleaver, the soft-in soft-out channel decoder calculates the obtained external information of the coded bit according to the input prior information and a code structure, and the external information of the coded bit is used as prior information for the next iterative processing of the iterative receiver after passing through the interleaver;
B. in the subsequent iteration processing, the signal received by the receiver, the bit prior information output by the soft-in soft-out channel decoder in the last iteration and the channel fading matrix obtained by channel estimation are utilized, parallel soft interference deletion is carried out on the received signals, the sum of residual interference and noise of the received signals after the parallel soft interference deletion is used as equivalent noise, each component of the equivalent noise is approximate to a mutually independent Gaussian random variable, soft-in soft-out minimum mean square error parallel soft interference cancellation multi-in multi-out MMSE PSIC MIMO detection calculation is carried out under the model, deinterleaves the outer information of the coded bits output by MMSE PSIC MIMO detection calculation, outputs the deinterleaved result to a soft-in soft-out channel decoder as prior information, the soft-in soft-out channel decoder calculates the posterior information and the external information of the coding bits according to the prior information and the code structure;
C. b, hard judgment is carried out on the posterior information of the coded bits output by the soft-in soft-out channel decoder, CRC (cyclic redundancy check) is carried out, and if the coded blocks are not correct and the number of iterations is smaller than the total number of iterations N, the step B is returned; otherwise, entering the step D;
D. and after the iterative detection is finished, outputting a result of hard decision of the posterior information of the coded bit as a final result of the iterative detection.
2. The method of claim 1, wherein the initial iterative process and the subsequent iterative process each comprise: the soft-in soft-out MIMO detector calculates the external information of the coded bits by utilizing the signals received by the receiver, the channel fading matrix obtained by channel estimation and the prior information output by the soft-in soft-out channel decoder in the last iteration processing, and the external information becomes the input prior information of the soft-in soft-out channel decoder after passing through a de-interleaver; and the soft-in soft-out channel decoder calculates the obtained external information of the coded bits according to the prior information and the code structure, and the external information is used as the prior information after passing through the interleaver for the next iteration processing of the iteration receiving.
3. The method of claim 2, wherein the a priori information output by the soft-in and soft-out channel decoder in the initial iteration process is 0 in the last iteration process.
4. The method of claim 1, wherein the subsequent iteration process is performed such that the calculation of the weight vector during the soft-in and soft-out MMSE PSIC MIMO detection calculation does not include matrix inversion.
5. The method of claim 4, wherein the soft-in soft-out MMSE PSIC MIMO detection computation process comprises the steps of:
calculating the mean value E(s) of all symbols to be detected according to the bit prior information output by the soft-in and soft-out channel decoder in the last iterationi) Sum variance var(s)i)，(i＝1，2，L，Nt) (ii) a According to E(s)i) Calculating a signal r received by the receiver and a channel fading matrix H obtained by channel estimation to obtain a symbol s after the receiving end is processed by PSICkEquivalent single-transmitting multi-receiving signal rkThe following were used:
calculating a signal skIs estimated value ofWherein
The ith element is calculated by the following formula (2):
wherein,
the mapping to symbol s is calculated according to the formulas (4) and (5)kOuter information of coded bits
μS-MMSE(k)＝wkhk
Wherein,
6. method according to claim 5, characterized in that said symbol skEquivalent single-transmitting multi-receiving signal rkIn the calculation of (1), a symbol soft estimate value E(s)i) Obtained by the following process:
bit prior information lambda output by soft-in soft-out channel decoder2[bπ(i)]Calculating a soft estimate E(s) of the symbol according to the principle of averagingi) The estimated value is used as prior information of MMSE PSIC MIMO detection:
。
7. the method of claim 6, wherein the variance of the soft estimate of the symbol in equation (3) is obtained by:
using a priori information lambda2[bπ(i)]According to the principle of averaging, a soft estimate of the sign modulo square is calculated:
calculating the variance of the symbol soft estimation value according to the variance calculation formula by using the symbol soft estimation value and the soft estimation value of the symbol modulus square obtained by calculation of the formulas (8) and (9):
var(si)＝E(|si|2)-E(si)2(i＝1，2，…，Nt) (10)。
8. the method of claim 1, wherein the total number of iterations is a preset fixed number or is adaptively determined according to a certain criterion during the iteration.
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