KR100989888B1 - Signal Detection Method for Multiple Input Multiple Output Systems - Google Patents

Abstract

The present invention relates to a signal detection method of a multiple input multiple output system, comprising: receiving a signal transmitted through a multiple input multiple output channel; Initializing a PED (partial Euclidean distance) value of each node of the received signal; Calculating a PED value based on a symbol of a node found at a predetermined level of each node and a symbol of a node found at a previous level; Selecting K predetermined PED values in a small order; And storing the selected K symbol pairs. This makes it possible to reduce the detection complexity and improve the accuracy of the detected signal when detecting the optimal candidate group for detecting spatially multiplexed data.

Description

Signal detecting method for multiple input multiple output system

The present invention relates to a signal detection method of a multiple input multiple output system, and more particularly, to a multiple input multiple output system for transmitting and receiving signals in a space-division multiplexing scheme. The present invention relates to a signal detection method of a multiple input multiple output system capable of reducing the detection complexity and improving the accuracy of a detected signal when detecting an optimal candidate group to detect spatially multiplexed data.

As high quality and high speed data transmission is required in a wireless communication environment, a multiple-input multiple output (MIMO) system using multiple antennas is used to efficiently use a limited frequency. have.

The MIMO system may be operated by space-time coding or space-division multiplexing. Spatio-temporal coding is a technique that can improve the reliability of wireless communication systems by encoding data transmitted from different antennas. Space-division multiplexing is a technique for increasing data rate by simultaneously transmitting data independent of each antenna.

In case of transmitting an independent symbol for each transmitting antenna through spatial division multiplexing in a MIMO system, various techniques for detecting a transmitting symbol from the receiving symbol at the receiving end have been proposed. In particular, the ML (Maximum Likelihood) detection technique is a technique that calculates and compares Euclidean distance with respect to symbol vectors in all cases that can be transmitted for symbol detection. However, as the number of antennas and the size of the modulation scheme increase, the complexity increases exponentially, which makes the implementation very difficult.

In order to reduce the complexity of such ML detection, a sphere decoding technique has been developed. The sphere decoding technique reduces the complexity of ML detection by performing Euclidean distance calculation only on a set of symbol vectors existing in a sphere having an initially set radius in consideration of noise variance and channel conditions.

In general, spear decoding techniques can be classified into depth-first search and width-first search.

The depth-first search algorithm can reduce the complexity of ML detection by tree searching back and forth. However, the digital circuit cannot be implemented by using a pipeline characteristic that can increase throughput, and since the calculation amount is variable, there is a problem that a search having a complexity of ML detection has to be performed in the worst case.

The breadth-first search algorithm, on the other hand, is designed to find the best candidate only in the forward direction. In particular, the K-best sphere decoding algorithm stores only the K best candidates at each tree search level.

FIG. 1 is a node selection state diagram according to a conventional sphere decoding method, and illustrates a process of selecting an optimal candidate group according to a K-best sphere decoding algorithm.

As shown in FIG. 1, nodes 1, 3, 5, and 7 exist at level i , and each node has a cumulative partial Euclidean distance (PED) value of 0.2, 0.3, 0.4, and 0.5. Here, node 7 is eliminated from the candidate group because the PED value is the highest as 0.5.

When calculating the new value PED selected candidate nodes are expanded to a level i-1 from the level i, and again updates the candidate node is selected nodes 2, 4, 6. Here, node 8 has a PED value of 0.55 and node 6 has a PED value of 0.7. Since node 8 has a lower PED value, but node 7 has already been discarded at level i , the best candidates for both levels of discovery are Node pairs (1, 2), (3, 4), (5, 6).

The K-best sphere decoding algorithm has a merit that a pipeline can be constructed to obtain a constant throughput. However, if the K value is large enough to achieve near-ML receiver performance, it still has high complexity. Thus, if a small K value is applied to make the implementation more suitable, the decoding delay is increased even though the performance degradation may occur due to the error transfer of the previous level and the throughput may be kept constant.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problem, and is a spatially multiplexed data in a multiple-input multiple-output system that transmits and receives a signal in a space-division multiplexing scheme. It is an object of the present invention to provide a signal detection method of a multi-input multiple output system capable of reducing the detection complexity and improving the accuracy of a detected signal when detecting an optimal candidate group.

A signal detection method of a multiple input multiple output system according to the present invention for achieving the above object comprises the steps of: receiving a signal transmitted through a multiple input multiple output channel; Initializing a PED (partial Euclidean distance) value of each node of the received signal; Calculating a PED value based on a symbol of a node found at a predetermined level of each node and a symbol of a node found at a previous level; Selecting K predetermined PED values in a small order; And storing the selected K symbol pairs.

Here, the operation of calculating the PED value based on the symbol of the node searched at the previous level of the tree search and the symbol of the node searched at the current level, level i = M, M-1, M-2, ..., 1 In the case of PED L _i (s ^(j-1) ) at the level i , it is possible to calculate by the following equation (6).

&Quot; (6) "

는 트리 탐색의 이전 레벨에서 찾아진 심벌의 부분 벡터이다.Where j = 2i,

Is the partial vector of symbols found at the previous level of tree traversal.

Further, calculating the PED value based on the symbol of the node searched at the previous level of the tree search and the symbol of the node searched at the current level, level i = M, M-1, M-2, ..., 1 In the case of PED L _i (s ^(j-1) ) at the level i , it is possible to calculate by the following equation (7).

[Equation 7]

항과

항은 이전 레벨에서 검출된 s ^(j+1) 에 의해서만 영향을 받는다.here,

Section

The term is only affected by s ^{(j + 1)} detected at the previous level.

On the other hand, the step of selecting the K predetermined PED values in the order of small size, the step of sorting the calculated PED values in ascending order; It is possible to include the step of selecting the K in the order of the smallest of the sorted PED value.

And after storing the selected K symbol pairs, calculating a PED value based on a symbol of a node found at a next level and a next level of the level at which the operation is completed; Selecting K predetermined PED values in a small order; It is possible to further include storing the selected K symbol pairs.

Further, the K value at the first level of the tree may be one.

As described above, the signal detection method of the multiple input multiple output system of the present invention is a multiple-input multiple output (Multiple-Input Multiple-Output) system for transmitting and receiving signals in a space-division multiplexing method, When the optimal candidate group is detected to detect spatially multiplexed data, symbol detection is simultaneously performed at two levels during the tree search. Accordingly, the accuracy of the detected signal can be improved by excluding the possibility of potential candidate groups being deleted, and the number of search levels can be reduced by half to reduce detection complexity.

Hereinafter, a signal detection method of a multiple input multiple output system according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, in describing the present invention, when it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

2 is an optimal candidate node selection state diagram according to a signal detection method of a multiple input multiple output system of the present invention.

As shown in Fig. 2, in the present invention, searching is performed at two levels simultaneously to select an optimal candidate group. That is, the search for nodes 2, 4, 6 and 8 present in the nodes 1, 3, 5, 7 and a level i-1 present in the level i and at the same time to choose the best candidate node pair.

At level i, there are nodes 1, 3, 5, and 7, and each node has a cumulative PED of 0.2, 0.3, 0.4, and 0.5. At level i-1 , nodes 2, 4, 6, and 8 exist, and each node has a cumulative PED value of 0.3, 0.4, 0.7, and 0.55.

Therefore, when the search for a node of a node and a level i-1 of level i at the same time, the node pair final cumulative PED value of (7,8) is 0.55, and the current level because the final cumulative PED 0.7 the nodes (5, 6) The finally selected candidate groups of are (7, 8), (1, 2), (3, 4).

As described above, the present invention simultaneously performs symbol detection at two levels during tree search in order to exclude the possibility that potential candidate groups that can help improve performance in the process of finding an optimal candidate group are deleted. At each level of the search, K _i symbol pairs are maintained. Compared with the conventional algorithm, the number of search levels of the proposed algorithm is reduced by half, and the performance is improved because the symbol search space for searching for potential candidates is expanded.

As described above, a multiple-input multiple-output (MIMO) system to which the present invention is applied consists of M transmit antennas and N receive antennas, and a baseband N-dimensional receive symbol. A vector can be represented by [Equation 1].

는 M차원 송신 신호 벡터이고 각 신호성분들은 BPSK, QPSK, 16-QAM, 64-QAM과 같은 복소성좌도 내에서 독립적으로 나타나는 심벌이다.

는 N×M 채널 행렬이고, 행렬 내의

는 j번째 송신안테나와 i번째 수신안테나 사이의 전달함수이다. 모든

는 각 차원마다 평균값이 0이고 분산이 0.5인 i.i.d 복소 랜덤 가우시안 변수이고, 수신기에서는 이 채널 정보를 모두 알고 있다고 가정한다.

는 평균 0, 분산

인 i.i.d 복소 가우 시안 잡음이다. [수학식 1]의 복소수 형태의 식은 아래의 [수학식 2]로 나타낼 수 있다.here

Is an M-dimensional transmission signal vector and each signal component is a symbol that appears independently in a complex locus such as BPSK, QPSK, 16-QAM, and 64-QAM.

Is an N × M channel matrix, and

Is a transfer function between the j th transmit antenna and the i th receive antenna. all

Is an iid complex random Gaussian variable with an average value of 0 and a variance of 0.5 for each dimension, and assume that the receiver knows all of this channel information.

Is an average of 0, variance

Iid is a complex Gaussian noise. The complex form of Equation 1 may be represented by Equation 2 below.

과

는 (ㆍ)의 실수부와 허수부이다. n을 2N, m을 2M이라 할 경우, [수학식 2]의 N×M채널 행렬

는 아래의 [수학식 3]과 같이 QR분할방식으로 삼각행렬로 표현할 수 있다.here

and

Is the real part and the imaginary part of (·). When n is 2N and m is 2M, the N × M channel matrix of Equation 2

Can be expressed as a triangular matrix by the QR division method as shown in Equation 3 below.

를 곱하면 다음의 [수학식 4]와 같이 표현할 수 있다.Where R is an n × m upper triangular matrix and Q is an n × m matrix with orthogonal columns. In [Equation 2]

By multiplying it can be expressed as Equation 4 below.

이고

이다. MIMO 검출의 목적은 성상도 상에서 가장 가까운 심벌위치,

를 찾는 것이고 이는 [수학식 5]와 같이 나타낼 수 있다.here

ego

to be. The purpose of MIMO detection is to locate the nearest symbol position on the constellation,

This can be expressed as [Equation 5].

에서 정의된다.Where the value of each s is the point Ω in real constellation

Is defined in.

In the MIMO system having such a configuration, the signal detection method of the multiple input multiple output system according to the present invention is as shown in FIG.

3 is a flowchart of a signal detection method of a multiple input multiple output system of the present invention.

First, the initial PED L _{M +1} = 0, input y, R is set to initialize the PED value (S10).

The PED value is calculated at each level i (S12). Here, when i = M, M-1, M-2, ..., 1. PED L _i (s ^(j-1) ) at the level i may be calculated as shown in [Equation 6].

&Quot; (6) "

는 트리 탐색의 이전 레벨에서 찾아진 심벌의 부분 벡터이다. [수학식 6]은 [수학식 7] 같이 다시 나타낼 수 있다.Where j = 2i. In [Equation 6]

Is the partial vector of symbols found at the previous level of tree traversal. Equation 6 may be represented again as in Equation 7.

[Equation 7]

항과

항은 이전 레벨에서 검출된 s ^(j+1) 에 의해서만 영향을 받는다. Ω가 Q개이고 레벨 i-1에서 K _{i -1} 개의 후보군 s ^(j+1) 을 갖는다면, 이 단계에서 전체 PED 값의 개수는 G= K _{i -1} ×Q가 된다.In [Equation 7]

Section

The term is only affected by s ^{(j + 1)} detected at the previous level. If Ω is Q and has K _{i -1} candidate groups s ^{(j + 1)} at level i-1 , the total number of PED values at this stage is G = K _{i -1} x Q.

When the PED operation is completed, the PED L _i (s ^(j-1) ) is sorted in ascending order and the minimum value of K _i is selected (S14).

Stores the determined K _i of symbol pairs (s _j, s _{j -1)} by the PED value (S16).

Thereafter, the process returns to step S12 to store the best pair of symbols, and if i = 1 because level 1 is the last level of the tree search, then K ₁ = 1 and signal search ends (S18).

As described above, the signal detection method of the present invention simultaneously searches for a predetermined level of tree search and a previous level to detect an optimal node pair having a small PED value. Therefore, when searching sequentially one level at a time, it is possible to prevent the candidate group of intermediate stages that affect the performance improvement from being discarded.

4 is a graph illustrating simulation results according to a signal detection method and a conventional spear decoding method of a multi-input multiple output system according to the present invention.

When 16-QAM modulation is used in a 4x4 MIMO system, the BER (Bit Error Rate) performance of the conventional spear decoding algorithm and the proposed algorithm is shown. It can be seen that the proposed algorithm, which extends the search range of candidate groups, shows better performance in terms of BER.

In the present invention, performing a simulation with a variety of K _i values in order to analyze the impact on the system performance of the proposed algorithm K _i values.

5 is a graph illustrating simulation results according to Ki values in a signal detection method of a multiple input multiple output system according to an exemplary embodiment of the present invention.

Initialize three different K _i values in the proposed MIMO detector ( K ₁ = 1, K ₂ = 4, K ₃ = 4, K ₄ = 4), ( K ₁ = 1, K ₂ = 5, K ₃ = 5, K ₄ = 5), ( K ₁ = 1, K ₂ = 6, K ₃ = 6, K ₄ = 6) shows the change in BER that appears. A K _i as shown in Fig. _{5 (K 1 = 1, K} 2 = 6, K 3 = 6, K 4 = 6) can be seen to have the best performance when set, the smaller K _i value of the deterioration of the performance You can see the import. If the proposed MIMO detector has a sufficiently large K _i value, it can be seen that the BER curve is close to the depth-first algorithm proposed by Damen et al.

As described above, the present invention simultaneously performs symbol detection at two levels during the tree search in order to exclude the possibility that potential candidate groups that can help improve performance in the process of finding an optimal candidate group are deleted. At each level, K _i symbol pairs are maintained. Compared with the conventional algorithm, the number of search levels of the proposed algorithm is reduced by half, and the performance is improved because the symbol search space for searching for potential candidates is expanded.

Although the present invention has been described in detail with reference to exemplary embodiments above, those skilled in the art to which the present invention pertains can make various modifications to the above-described embodiments without departing from the scope of the present invention. Will understand. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined not only by the claims below but also by the equivalents of the claims.

1 is a node selection state diagram according to a conventional sphere decoding method

2 is an optimal candidate node selection state diagram according to a signal detection method of a multiple input multiple output system of the present invention;

3 is a flowchart of a signal detection method of a multiple input multiple output system of the present invention;

4 is a graph of simulation results according to a signal detection method and a conventional spear decoding method of a multiple input multiple output system according to the present invention;

5 is a graph illustrating simulation results according to Ki values in a signal detection method of a multiple input multiple output system according to an exemplary embodiment of the present invention.

Claims (6)

Receiving a signal transmitted over a multiple input multiple output channel; Initializing a PED (partial Euclidean distance) value of each node of the received signal; Calculating a PED value based on a symbol of a node found at a predetermined level of each node and a symbol of a node found at a previous level; Selecting K predetermined PED values in a small order; Storing the selected K symbol pairs, Selecting the predetermined K PED values in the order of the smallest size, Sorting the calculated PED values in ascending order; And selecting the K from the sorted PED values in order of decreasing magnitude. The method of claim 1, Computing a PED value based on a symbol of a node found at a predetermined level of each node and a symbol of a node found at a previous level, When level i = M, M-1, M-2, ..., 1. and PED L _i (s ^(j-1) ) at level i , it is calculated by Equation 6 below. A signal detection method of a multiple input multiple output system characterized by the above-mentioned.

Where j = 2i,

Is the partial vector of symbols found at the previous level. The method of claim 1, Computing a PED value based on a symbol of a node found at a predetermined level of each node and a symbol of a node found at a previous level, When level i = M, M-1, M-2, ..., 1. and PED L _i (s ^(j-1) ) at level i , it is calculated by the following formula (7). A signal detection method of a multiple input multiple output system characterized by the above-mentioned. [Equation 7]

here,

Section

The term is only affected by s ^{(j + 1)} detected at the previous level. delete The method of claim 1, After storing the selected K symbol pairs, calculating a PED value based on a symbol of a node found at a next level and a next level of the level at which the operation is completed; Selecting K predetermined PED values in a small order;  And storing the selected K symbol pairs. The method of claim 5, And the K value at the first level is one.

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