CN102594467A - Receiver detection method for wireless multiple input multiple output system - Google Patents

Abstract

The invention provides a receiver detection method for a multiple input multiple output system. The method comprises the following steps of: carrying out QR decomposition on a channel matrix H so as to obtain a matrix Q and an upper triangular matrix R; multiplying the conjugate transpose of the matrix Q by the vector y of a receiver signal so as to obtain a balance signal of the receiver signal; building an LUT (lookup table) of a node expansion sequence and setting the radius of sphere decoding, wherein the size of an available memory space is M; calculating a search center, and obtaining a subscript of the LUT according to the search center and a demodulation manner so as to obtain an initial selected node; removing the selected node out of a stack, and updating the radius of the sphere decoding according to expanded brother nodes and child nodes of the selected node; judging whether the selected node is a leaf node or not so as to maintain a soft value table; selecting a node for next iteration; and calculating LLR value according to the soft value table. According to the receiver detection method, on the premise of guaranteeing the performance of the system, the complexity of the receiver is effectively lowered.

Description

The receiver detection method of wireless multiple-input-multiple-output systems

Technical field

What the present invention relates to is a kind of method of wireless communication technology field, relates to a kind of receiver detection method of wireless multiple-input-multiple-output systems particularly.

Background technology

Traditional multiple-input and multiple-output (Multiple Input Multiple Output; MIMO) technology; Be through utilizing the multi-antenna structure of base station and user side, realization branch collection and space division multiplexing, thereby a kind of technology of increase throughput of system; Because become 3GPP-LTE, the research focus of IEEE 802.16e WIMAX.In recent years, along with the development of turbo decoding and LDPC decoding technique, the decoding of MIMO receiver and the technological error rate that combines significantly to reduce system of channel decoding.Maximum Likelihood Detection (ML) is optimum receiver detection algorithm, but the complexity that ML detects increases along with number of transmit antennas and order of modulation are exponential type.The linearity test algorithm of suboptimum though complexity is low, all can not reach reception full marks intensity as compeling zero (ZF) and least mean-square error (MMSE) criterion, and performance is far below the ML detection algorithm.Soft output method for detecting spherical decode in the multi-input multi-output system can significantly reduce the complexity of system.

Through existing literature search is found; Studer.C etc. are at " IEEE Transaction on Information Theory " (U.S. electric and Electronic Engineering Association's information theory periodical; October the 56th in 2010, volume was the 4827th to the 4842nd page) on, delivered " Soft-Input Soft-Output Single Tree-Search Sphere Decoding " (" soft input globular decoding of soft output of single tree search "), this article has proposed; In many antennas multi-input multi-output system; Soft value and the ML that in search procedure, dynamically updates each bit be the value of declaring firmly, and the document has proved that STS globular decoding algorithm performance is optimum, and guarantees that each node only needs by visit once; But still complexity is higher for this soft output globular decoding, is difficult for realizing.Find through retrieval again; Markus M etc. are at " Signal Processing " (signal processing magazine; October the 90th in 2010, volume was the 2863rd page to the 2876th page) on; Delivered " Implementation aspects of list sphere decoder algorithms for MIMO-OFDM systems " (" application of tabulation globular decoding in the MIMO-OFDM system "); This article calculates soft value through the tabulation globular decoding of K-Best globular decoding or Dijkstra (Di Jiesitela) globular decoding algorithm; But during the tabulation globular decoding can not guarantee to tabulate ML firmly the bit polarity of the value of declaring necessarily have on the contrary, cause the error of calculation of LLR value, influence systematic function.

Summary of the invention

The objective of the invention is to overcome the above-mentioned deficiency of prior art, a kind of soft output globular decoding algorithm of low complex degree is provided, reduce the complexity of receiver.The present invention combines Dijkstra globular decoding algorithm to be generalized to the soft output globular decoding of single tree search; Through structure look-up table LUT (Look Up Table); Improve the node expanded search algorithm of Dijkstra globular decoding, obtained the ML value of declaring and LLR value firmly apace, reduced the search volume; Reduced the receiver complexity, and performance detects with ML consistent.The present invention has in accurate ML performance and the low characteristics of complexity, and is suitable for the characteristics of various multi-input multi-output systems.

According to an aspect of the present invention, the receiver detection method of said wireless multiple-input-multiple-output systems may further comprise the steps:

Step 1: channel matrix H is carried out QR decompose, obtain Q matrix and upper triangular matrix R; The conjugate transpose and the received signal vector y of Q matrix are multiplied each other, obtain receiving the equalizing signal

of signal

Step 2: the look-up table LUT (Look Up Table) that sets up node expansion order;

Step 3: calculate search center, obtain the subscript of look-up table, initially chosen node, be pressed in the stack according to search center and modulation system;

Step 4: from stack, remove and choose node, and according to the expansion brotgher of node of choosing node, upgrade radius, whether the radius of judging present node is then to cut down present node and all branches thereof, otherwise the brotgher of node is pressed in the stack less than the current search radius;

Step 5: judge and choose whether node is leaf node, if leaf node then carries out the maintenance of soft value table; Otherwise downward one deck expanded search; Calculate the subscript that search center and modulation system obtain look-up table, obtain child node, whether the radius of judging present node is less than the current search radius; Be then to cut down present node and all branches thereof, otherwise child node is pressed in the stack;

Step 6: whether disconnected current stack is empty, if be empty, then arrives step 7; Otherwise according in the stack memory space and the weights node of selecting next iteration to choose, return step 5;

Step 7: carry out the LLR value according to soft value table and calculate.

Preferably, in said step 2, the look-up table establishment step is:

Hypothesis tree searches the i layer, then the part vector

Known, definition c _iIt is the search center of i layer

$c_i=\frac{1}{r_{\mathrm{Ii}}}({\stackrel{\·}{y}}_i-\underset{n=i+1}{\overset{N_R}{\mathrm{\Σ}}}{r}_{\mathrm{In}}{s}_n)$ Formula one

Then said formula one is rewritten as:

$d_i=d_{i+1}+{\mathrm{<figure-callout\; id="2"\; label="r\; Ii"\; filenames="HDA0000137383210000011.png,HDA0000137383210000042.png"\; state="\{\{state\}\}">r</figure-callout>}}_{\mathrm{Ii}}^{}{|c_i-s_i|}^2$ Formula two

Node is at first visited range search center c _iNearest constellation point s _i, then according to c _iOrder from the near to the remote carries out the sorted search visit; Confirm that when the modulation system of mimo system the modulation symbol collection is promptly definite, thereby can be according to c _iArrange the expansion of constellation point in proper order in the belonging positions zone, sets up look-up table LUT; Wherein, The zone of each constellation point is divided into 4, from the near to the remote the visit order of constellation point is arranged according to the distance in space, the look-up table size that 4-QAM needs is 16; The look-up table size that 16-QAM needs is 64, and the look-up table size that 64-QAM needs is 256.

Preferably, in said step 3 and step 5, search center computational process is:

Hypothesis tree searches the i layer, then the part vector

Known, definition c _iIt is the search center of i layer

$c_i=\frac{1}{r_{\mathrm{ii}}}({\stackrel{\&CenterDot;}{y}}_i-\underset{n=i+1}{\overset{N_R}{\mathrm{\&Sigma;}}}{r}_{\mathrm{in}}{s}_n).$

Preferably, in said step 3 and step 4, the node expansion process is:

Suppose that it is N that current stack is wanted the node of downward one deck expansion _c=(s=s ⁽ⁱ⁾, d (s), p, q; I), remaining space is M in the stack, and wherein s is current solution vector, and i is the number of plies that present node is positioned at; P and q are respectively in the subscript of current selected look-up table and the present node subscript in the constellation point of i layer, and wherein, the node extended method comprises following substep:

1) from stack, removes node N _c=(s=s ⁽ⁱ⁾, d (s), p, q, level=i), M=M+1 expands level=i layer and the nearest node of node N, even s _f=(LUT (p, q+1), s ⁽ⁱ⁺¹⁾), calculate d (s _f), if d is (s _f)＜R ₀With node N _f=(s=s _f, d (s _f), p, q=q+1 level=i) deposits in the stack M=M-1 in;

2) if node N _cBe leaf node when being i=1, carry out the LLR value and upgrade with ML and separate renewal, otherwise downward one deck is expanded, through following formula

$d_i=d_{i+1}+{\mathrm{<figure-callout\; id="2"\; label="r\; ii"\; filenames="HDA0000137383210000011.png,HDA0000137383210000042.png"\; state="\{\{state\}\}">r</figure-callout>}}_{\mathrm{ii}}^{}{|c_i-s_i|}^2$

Calculate search center c _I-1, obtain look-up table subscript p, make s _Exp=(LUT (p, 0), s ⁽ⁱ⁾), calculate d (s _Exp), if d is (s _Exp)＜R ₀With node N _Exp=(s=s _Exp, d (s _Exp), p, q=0 i-1) deposits in the stack M=M-1 in.

Preferably, in said step 3 and step 4, the radius renewal process is:

Radius upgrades and is divided into two parts:

1) for known portions vector, i.e. k>=i, m=1,2 ..., Q, radius R ₀With

Relevant, promptly

${\mathrm{<figure-callout\; id="0"\; label="R"\; filenames="HDA0000137383210000021.png,HDA0000137383210000031.png"\; state="\{\{state\}\}">R</figure-callout>}}_0=\max \left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k\&GreaterEqual;i,m=\mathrm{1,2}...,Q,s_{k,m}=s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\};$

2) for the part vector that does not also have search, i.e. k＜i, m=1,2 ..., Q, radius R ₀With all

Relevant, promptly

${\mathrm{<figure-callout\; id="0"\; label="R"\; filenames="HDA0000137383210000021.png,HDA0000137383210000031.png"\; state="\{\{state\}\}">R</figure-callout>}}_0=\max \left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k<i,m=\mathrm{1,2},...,Q\}.$

Preferably, in said step 4, soft value table renewal process is:

Be initialized as $d\left(s^{\mathrm{ML}}\right)=d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=\&infin;(\&ForAll;k,m),$ Divide two kinds of situation:

1) when obtaining a new ML and separate, i.e. d (s)＜d (s ^ML), then all are met

Bit Be updated to

And upgrade s ^ML=s and d (s ^ML)=d (s);

2) if d (s)＞d (s ^ML), only need this moment to upgrade

Value, when

And

The time, upgrade

$d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=d\left(s\right).$

Preferably, in said step 6, node selecting method is:

Make n _Max=min (M+2, N _T), the node in the stack is sorted according to d (s) from small to large, select to have minimum d (s) and satisfy i＜n _MaxNode, establishing the node of choosing is N _c

Preferably, in said step 7, the LLR value calculating method is:

For $\&ForAll;k\&Element;\{1,...,N_T\},$ $\&ForAll;m\&Element;\{1,...,Q\},$ Utilize computes LLR value

$L\left(b_{k,m}\right)=\left\{\begin{array}{c}d\left(s^{\mathrm{ML}}\right)-d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right),s_{k,m}^{\mathrm{ML}}=-1\\ d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)-d\left(s^{\mathrm{ML}}\right),s_{k,m}^{\mathrm{ML}}=+1\end{array}\right..$

Description of drawings

Schematic diagram for the foundation of the inventive method look-up table shown in Figure 1;

Shown in Figure 2 is under 4 * 4MIMO system, under the QPSK modulation, and the error rate contrast sketch map of different receivers detection method;

Shown in Figure 3 is under 4 * 4MIMO system, under the 16QAM modulation, and the error rate contrast sketch map of different receivers detection method;

Shown in Figure 4 is under 4 * 4MIMO system, and under the QPSK modulation, the search volume of different receivers detection method is to the sketch map of complexity contrast when;

Shown in Figure 5 is under 4 * 4MIMO system, and under the 16QAM modulation, the search volume of different receivers detection method is to the sketch map of complexity contrast when;

Shown in Figure 6 is the wireless multiple-input-multiple-output systems block diagram;

Shown in Figure 7 is performing step block diagram of the present invention.

Embodiment

With reference to the accompanying drawings embodiments of the invention are elaborated, in the description process, having omitted is unnecessary details and function for the present invention, obscures to prevent understanding of the present invention caused.Provide specific embodiment of the present invention below, be applicable to long evolving system and advance the rank long evolving system.Need to prove, the invention is not restricted to the application described in the embodiment, also use MIMO technique and the wireless communication system that receives detection technique applicable to other.

Embodiment

For making the object of the invention, technical scheme and advantage are clearer, describe the present invention below in conjunction with accompanying drawing and practical implementation instance.

The system model that present embodiment adopts is for having N _TIndividual transmitting antenna N _RThe mimo system of individual reception antenna is without loss of generality, and makes N _R=N _T, the emission information bit obtains N through channel coding module behind interleaver module and string and the conversion modulation module _T* 1 emission signal vector

Wherein Ω is the modulation symbol collection, | Ω |=2 ^Q(Q is an order of modulation).Corresponding N _R* 1 received signal vector

So the model of mimo system is:

y＝Hs+n (1)

H in the formula (1) is a channel matrix, and n representes that average is 0, and variance is σ ²Gauss's additive white noise.

Channel matrix H is carried out the QR decomposition obtain H=QR, wherein R is a upper triangular matrix, and Q is an orthogonal matrix, and formula (1) formula can be write as

$\stackrel{\&CenterDot;}{y}=\mathrm{Rs}+\stackrel{\&CenterDot;}{n}---\left(2\right)$

Wherein

Definition

Be vector

I element, r _Ij(i, j) individual element for upper triangular matrix R.The definitional part signal vector

Vector s ⁽ⁱ⁾Regard the node of one tree as, establish i=N _T+ 1 layer is root node, and the i=1 layer is a leaf node, and each node has 2 ^QNode, each leaf node s ⁽¹⁾It all is a solution vector.Euclidean distance

can obtain through part of Euclidean distance (PED) iterative computation:

d _i＝d _i+1+|e _i| ²，i＝N _T，N _T-1，…，1 (3)

${\left|e_i\right|}^2={|{\stackrel{\&CenterDot;}{y}}_n-\underset{n=i+1}{\overset{N_R}{\mathrm{\&Sigma;}}}{r}_{\mathrm{in}}{s}_n-r_{\mathrm{ii}}{s}_i|}^2---\left(4\right)$

D (s)=d wherein ₁, Be initialized as 0.

The MIMO receiver is exported the Bit data b that makes a start _{K, m}, k ∈ 1 ..., N _T, m ∈ 1 ..., the soft value of Q} estimates that the definition of the soft value LLR of max-log (Log Likelihood Ratio) is:

$L\left(b_{k,m}\right)\&ap;\frac{1}{{\mathrm{\&sigma;}}_n^2}[\underset{s\&Element;S_{k,m}^{-1}}{\min }{\left|\right|y-\mathrm{Hs}\left|\right|}^2-\underset{s\&Element;S_{k,m}^{+1}}{\min }{\left|\right|y-\mathrm{Hs}\left|\right|}^2]---\left(5\right)$

$\&ap;\frac{1}{{\mathrm{\&sigma;}}_n^2}[\underset{s\&Element;S_{k,m}^{-1}}{\min }{\left|\right|\stackrel{\&CenterDot;}{y}-\mathrm{Rs}\left|\right|}^2-\underset{s\&Element;S_{k,m}^{+1}}{\min }{\left|\right|\stackrel{\&CenterDot;}{y}-\mathrm{Rs}\left|\right|}^2]$

In the formula (5), L (b _{K, m}) represent that emission is to quantity symbol s _kThe LLR value of m bit,

Represent the symbol s among the vectorial s _kThe value of m bit is ± 1 set.Observed and can be obtained by formula (5), one of them minimum value is that ML separates s ^MLEuclidean distance $d\left(s^{\mathrm{ML}}\right)={\left|\right|\stackrel{\&CenterDot;}{y}-{\mathrm{Rs}}^{\mathrm{ML}}\left|\right|}^2,$ Wherein

$s^{\mathrm{ML}}=\underset{s\&Element;{\mathrm{\&Omega;}}^{N_T}}{\arg \min }{\left|\right|\stackrel{\&CenterDot;}{y}-\mathrm{Rs}\left|\right|}^2---\left(6\right)$

Another corresponding minimum value is:

$\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=\underset{s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}}{\min }{\left|\right|\stackrel{\&CenterDot;}{y}-\mathrm{Rs}\left|\right|}^2---\left(7\right)$

For launching to quantity symbol s _kThe polarity of m bit is s ^MLOpposite.So formula (2) can be rewritten as:

$L\left(b_{k,m}\right)=\left\{\begin{array}{c}d\left(s^{\mathrm{ML}}\right)-d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right),s_{k,m}^{\mathrm{ML}}=-1\\ d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)-d\left(s^{\mathrm{ML}}\right),s_{k,m}^{\mathrm{ML}}=+1\end{array}\right.---\left(8\right)$

If set

For meeting emission to quantity symbol s _kThe polarity of m bit is s ^MLThe set of opposite condition, then the search procedure can cost of equivalent place set of MIMO Maximum Likelihood Detection and max-log LLR value computational process is promptly being gathered

And set

Middle search has the leaf node of minimum Eustachian distance, obtains d (s ^ML) and N _T* Q

Value.

The embodiment of the invention has adopted based on the preferential soft output method for detecting spherical decode of Dijkstra of tolerance, and is as shown in Figure 7, comprises the steps:

Step 201: channel matrix H is carried out QR decompose, obtain Q matrix and upper triangular matrix R.

Step 202: the conjugate transpose and the received signal vector y of Q matrix are multiplied each other, and the equalizing signal i.e. that obtains receiving signal

carries out soft output globular decoding through the search tree that equivalent matrix R and equalizing signal make up.

Step 203: set up look-up table LUT, the radius R of globular decoding is set ₀=∞, available storage size is M.

Concrete look-up table LUT sets up process, and hypothesis tree searches the i layer, then the part vector

Known, definition c _iIt is the search center of i layer

$c_i=\frac{1}{r_{\mathrm{ii}}}({\stackrel{\&CenterDot;}{y}}_i-\underset{n=i+1}{\overset{N_R}{\mathrm{\&Sigma;}}}{r}_{\mathrm{in}}{s}_n)---\left(9\right)$

Then formula (9) is rewritten as:

$d_i=d_{i+1}+{\mathrm{<figure-callout\; id="2"\; label="r\; ii"\; filenames="HDA0000137383210000011.png,HDA0000137383210000042.png"\; state="\{\{state\}\}">r</figure-callout>}}_{\mathrm{ii}}^{}{|c_i-s_i|}^2---\left(10\right)$

Node is at first visited range search center c _iNearest constellation point s _i, then according to c _iOrder from the near to the remote carries out the sorted search visit.Confirm that when the modulation system of mimo system the modulation symbol collection is promptly definite, thereby can be according to c _iArrange the expansion of constellation point in proper order in the belonging positions zone, sets up look-up table LUT.For reducing the memory space of look-up table, the present invention is divided into 4 with the zone of each constellation point, from the near to the remote the visit order of constellation point is arranged according to the distance in space, and is as shown in Figure 1, is modulated to example with 16QAM, as search center c _iFall into diagonal line hatches when zone, 16 constellation point sort according to the distance of sequencing and shadow region, wherein; This order can change according to actual needs; This does not influence flesh and blood of the present invention, and for example among Fig. 1 (a), the order of constellation point " 9 " and " 10 " just might be changed; Simulation result shows then, and this approximate processing is to almost not influence of performance.In order to cover all possible constellation point in the QAM modulation, the look-up table size that 4-QAM needs is 16, and the look-up table size that 16-QAM needs is 64, and the look-up table size that 64-QAM needs is 256.

Step 204: calculate

According to

Reach the subscript p that modulation system obtains look-up table, obtain initial point

If memory node will $N_c=(s=s^{\left(N_T\right)},d\left(s\right),p,q=0,i=N_R),$ M=M-1.

Step 205: from stack, remove node N _c=(s=s ⁽ⁱ⁾, d (s), p, q, i), M=M+1 expands i layer and node N _cNearest node makes s _f=(LUT (p, q+1), s ⁽ⁱ⁺¹⁾), calculate d (s _f) according to current vectorial s _fUpgrade the radius R of globular decoding ₀If d is (s _f)＜R ₀, with N _f=(s=s _f, d (s _f), p, q=q+1 i) deposits in the stack M=M-1 in; Otherwise forward step 206 to.

The radius update method of the globular decoding of this step is:

When search tree obtains part solution vector

,, the radius of globular decoding is divided into two parts so upgrading

(1) for known portions vector, i.e. k>=i, m=1,2 ..., Q, radius R ₀With

Relevant, promptly

${\mathrm{<figure-callout\; id="0"\; label="R"\; filenames="HDA0000137383210000021.png,HDA0000137383210000031.png"\; state="\{\{state\}\}">R</figure-callout>}}_0=\max \left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k\&GreaterEqual;i,m=\mathrm{1,2},...,Q,s_{k,m}=s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\}$

(2) for the part vector that does not also have search, i.e. k＜i, m=1,2 ..., Q, radius R ₀With all

Relevant, promptly

${\mathrm{<figure-callout\; id="0"\; label="R"\; filenames="HDA0000137383210000021.png,HDA0000137383210000031.png"\; state="\{\{state\}\}">R</figure-callout>}}_0=\max \left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k<i,m=\mathrm{1,2},...,Q\}$

Step 206: if node N _cBe leaf node (i=1), upgrade soft value table

And s ^MLOtherwise one deck expansion downwards, through type (10) calculates search center c _I-1, obtain look-up table subscript p, make s _Exp=(LUT (p, 0), s ⁽ⁱ⁾), calculate d (s _Exp), according to s _ExpUpgrade radius R ₀(the radius update method is consistent with step 205).If d is (s _Exp)＜R ₀, with N _Exp=(s=s _Exp, d (s _Exp), p, q=0 i-1) deposits in the stack M=M-1 in; Otherwise forward step 207 to.

The process of the soft value table of the renewal in this step is:

Initialization

, the tree search obtains new solution vector s when arriving leaf node ⁽¹⁾Just carry out soft value table and upgrade, divide two kinds of situation:

(1) when obtaining a new ML and separate, i.e. d (s)＜d (s ^ML), then all are met

Bit

Be updated to

And upgrade s ^ML=s and d (s ^ML)=d (s).Guaranteed like this current at all and s ^MLOpposite bit

It all is current minimum value.

(2) if d (s)＞d (s ^ML), only need this moment to upgrade

Value, when

And

The time, with new $d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=d\left(s\right).$

Step 207: make n _Max=min (M+2, N _T), the node in the stack is sorted according to d (s) from small to large, select to have the node of minimum d (s) and satisfy number of plies i＜n _Max, establishing the node of choosing is N _cIf current stack is not M ≠ 0 for sky,, forward step 3 to; Otherwise forward step 205 to.

Step 208: the LLR value L (b that calculates each bit according to formula (5) _{K, m}), the output result.

Fig. 2, Fig. 3, Fig. 4, Fig. 5 are the globular decoding algorithm of the embodiment of the invention and the comparison of traditional several kinds of globular decoding algorithm performances and complexity.

Simulation parameter is following: channel adopts suburb macrocell SCM channel, and carrier frequency is 2GHz, and bandwidth is 3MHz, and chnnel coding adopts the turbo coding, and modulation system is QPSK and 16QAM, and code check is 378/1024, number of transmit antennas: 4, and reception antenna number: 4.

Fig. 2, Fig. 3 have provided the ber curve comparison of soft-decision under the distinct methods; The interpretation method that the present invention proposes is almost consistent with the performance of STS globular decoding method method; Than K-BEST tabulation globular decoding method; Performance has bigger lifting, and under high order modulation 16QAM, performance boost is obvious more.

Fig. 4, Fig. 5 have provided the comparison of the complexity of different receivers detection method; Complexity relatively be through search node in the search procedure number relatively; Visible by Fig. 4, Fig. 5, the interstitial content of the interpretation method search that the present invention proposes and the downward trend of STS-SD interpretation method are similar, but than the STS-SD interpretation method; The node number that the search volume was promptly visited reduces; And the amplitude of variation of the node number of visiting is compared less with the STS-SD interpretation method, and the hardware that is beneficial to estimating system is realized expense, decoding delay and throughput.Compare with being beneficial to hard-wired K-BSET tabulation globular decoding, the globular decoding method that the present invention proposes is under low-order-modulated (QPSK), and performance is better than K-BSET (64) globular decoding method, and the search node number still less.Under high order modulation (16QAM), performance is much better than K-BSET (16) globular decoding method, and search node to count increasing degree very little, hardware realize with performance on have preferably and compromise.

From Fig. 2, Fig. 3, Fig. 4, Fig. 5 comparative illustration, instance of the present invention is keeping having effectively reduced the complexity of system under the high performance prerequisite.

Claims (8)

1. the receiver detection method of a wireless multiple-input-multiple-output systems is characterized in that, comprising:

Step 1: channel matrix H is carried out QR decompose; Obtain Q matrix and upper triangular matrix R; The conjugate transpose and the received signal vector y of Q matrix are multiplied each other, obtain receiving the equalizing signal of signal

Step 2: set up the look-up table LUT of node expansion order, the radius of globular decoding is set, available storage size is M;

Step 3: calculate search center, obtain the subscript of look-up table LUT, initially chosen node, be pressed in the stack according to search center and modulation system;

Step 4: from stack, remove and choose node; And, upgrade the radius of globular decoding according to the expansion brotgher of node of choosing node, whether the radius of judging present node is less than the current search radius; Be then to cut down present node and all branches thereof, otherwise the brotgher of node is pressed in the stack;

Step 5: judge and choose whether node is leaf node, if leaf node then carries out the maintenance of soft value table; Otherwise downward one deck expanded search; Calculate the subscript that search center and modulation system obtain look-up table LUT, obtain child node, whether the radius of judging present node is less than the current search radius; Be then to cut down present node and all branches thereof, otherwise child node is pressed in the stack;

Step 6: judge that whether current stack is empty, if be empty, then arrives step 7; Otherwise according in the stack memory space and the weights node of selecting next iteration to choose, return step 5;

Step 7: carry out the LLR value based on soft value table and calculate.

2. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that,

In said step 2, the look-up table establishment step is:

Hypothesis tree searches the i layer, then the part vector

Known, definition c _iIt is the search center of i layer

$c_i=\frac{1}{r_{\mathrm{Ii}}}({\stackrel{\&CenterDot;}{y}}_i-\underset{n=i+1}{\overset{N_R}{\mathrm{\&Sigma;}}}{r}_{\mathrm{In}}{s}_n)$ Formula one

Then said formula one is rewritten as:

$d_i=d_{i+1}+r_{\mathrm{Ii}}^2{|c_i-s_i|}^2$ Formula two

Node is at first visited range search center c _iNearest constellation point s _i, then according to c _iOrder from the near to the remote carries out the sorted search visit; Confirm that when the modulation system of mimo system the modulation symbol collection is promptly definite, thereby can be according to c _iArrange the expansion of constellation point in proper order in the belonging positions zone, sets up look-up table LUT; Wherein, The zone of each constellation point is divided into 4, from the near to the remote the visit order of constellation point is arranged according to the distance in space, the look-up table size that 4-QAM needs is 16; The look-up table size that 16-QAM needs is 64, and the look-up table size that 64-QAM needs is 256.

3. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that,

In said step 3 and step 5, search center computational process is:

Hypothesis tree searches the i layer, then the part vector

Known, definition c _iIt is the search center of i layer

$c_i=\frac{1}{r_{\mathrm{ii}}}({\stackrel{\&CenterDot;}{y}}_i-\underset{n=i+1}{\overset{N_R}{\mathrm{\&Sigma;}}}{r}_{\mathrm{in}}{s}_n).$

4. the receiver detection method of wireless many defeated people's multiple output systems according to claim 1 is characterized in that,

In said step 3 and step 4, the node expansion process is:

Suppose that it is N that current stack is wanted the node of downward one deck expansion _c=(s=s ⁽ⁱ⁾, d (s), p, q; I), remaining space is M in the stack, and wherein s is current solution vector, and i is the number of plies that present node is positioned at; P and q are respectively in the subscript of current selected look-up table and the present node subscript in the constellation point of i layer, and wherein, the node extended method comprises following substep:

1) from stack, removes node N _c=(s=s ⁽ⁱ⁾, d (s), p, q, level=i), M=M+1 expands level=i layer and the nearest node of node N, even s _f=(LUT (p, q+1), s ⁽ⁱ⁺¹⁾), calculate d (s _f), if d is (s _f)＜R ₀With node N _f=(s=s _f, d (s _f), p, q=q+1 level=i) deposits in the stack M=M-1 in;

2) if node N _cBe leaf node when being i=1, carry out the LLR value and upgrade with ML and separate renewal, otherwise downward one deck is expanded, through following formula

$d_i=d_{i+1}+r_{\mathrm{ii}}^2{|c_i-s_i|}^2$

Calculate search center c _I-1, obtain look-up table subscript p, make s _Exp=(LUT (p, 0), s ⁽ⁱ⁾), calculate d (s _Exp), if d is (s _Exp)＜R ₀With node N _Exp=(s=s _Exp, d (s _Exp), p, q=0 i-1) deposits in the stack M=M-1 in.

5. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that, in said step 3 and step 4, the radius renewal process is:

Radius upgrades and is divided into two parts:

1) for known portions vector, i.e. k>=i, m=1,2 ..., Q, radius R ₀With

Relevant, promptly $R_0=\mathrm{Max}\left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k\&GreaterEqual;i,m=\mathrm{1,2},...,Q,s_{k,m}=s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\};$

2) for the part vector that does not also have search, i.e. k＜i, m=1,2 ..., Q, radius R ₀With all

Relevant, promptly $R_0=\mathrm{Max}\left\{d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)\right|\&ForAll;k<i,m=\mathrm{1,2},...,Q\}.$

6. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that,

In said step 4, soft value table renewal process is:

Be initialized as $d\left(s^{\mathrm{ML}}\right)=d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=\&infin;(\&ForAll;k,m),$ Divide two kinds of situation:

1) when obtaining a new ML and separate, i.e. d (s)＜d (s ^ML), then all are met

Bit Be updated to

And upgrade s ^ML=s and d (s ^ML)=d (s);

2) if d (s)＞d (s ^ML), only need this moment to upgrade

Value, when

And The time, upgrade $d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)=d\left(s\right).$

7. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that,

In said step 6, node selecting method is:

Make n _Max=min (M+2, N _T), the node in the stack is sorted according to d (s) from small to large, select to have minimum d (s) and satisfy i＜n _MaxNode, establishing the node of choosing is N _c

8. the receiver detection method of wireless multiple-input-multiple-output systems according to claim 1 is characterized in that,

In said step 7, the LLR value calculating method is:

For $\&ForAll;k\&Element;\{1,...,N_T\},$ $\&ForAll;m\&Element;\{1,...,Q\},$ Utilize computes LLR value

$L\left(b_{k,m}\right)=\left\{\begin{array}{c}d\left(s^{\mathrm{ML}}\right)-d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right),s_{k,m}^{\mathrm{ML}}=-1\\ d\left(s_{k,m}^{\stackrel{\&OverBar;}{\mathrm{ML}}}\right)-d\left(s^{\mathrm{ML}}\right),s_{k,m}^{\mathrm{ML}}=+1\end{array}\right..$

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