WO2009115042A1

WO2009115042A1 - Joint iterative detection and decoding method and device

Info

Publication number: WO2009115042A1
Application number: PCT/CN2009/070861
Authority: WO
Inventors: 曹晏波; 李洪强; 王鑫; 乔元新; 王映民; 孙建勋; 董育新
Original assignee: 大唐移动通信设备有限公司
Priority date: 2008-03-18
Filing date: 2009-03-18
Publication date: 2009-09-24
Also published as: CN101541023B; CN101541023A

Abstract

A joint iterative detection and decoding method includes:a, determining an optional constellation point number cj corresponding with each transmitting antenna, according to the number of detection signal vectors needed by joint iterative detection, the modulation exponent number M of transmitting antennas and the number of transceiver antennas, therein, cj=2M; b, choosing ?m j=1Cj detection signal vectors which have the minimum distance to the true transmitting signal in all detection signal vectors and forming a candidate collection list, according to the optional constellation point number cj corresponding with each transmitting antenna determined in the step a; c, calculating each information bit log-likelihood ratios using MAP bit detection arithmetic, according to all detection signal vectors in the candidate collection list.

Description

OP60-090015 A joint iterative detection decoding method and device

Technical field

The present invention relates to signal detection techniques for multiple input multiple output (MIMO) systems, and more particularly to a joint iterative detection decoding method and apparatus. Background of the invention

Detection techniques include linear detection, interference cancellation, lattice reduction aid detection, Monte Carlo statistics, probabilistic data joint detection, ball decoding detection and other optimal and sub-optimal detection methods. Usually detection and decoding at the receiving end are performed independently. The Turbo receiver uses iterative processing techniques to improve system performance by approaching channel capacity by external information transfer between the detector and the decoder.

For multi-user or multi-antenna systems, a similar iterative technique, i.e., a joint iterative detection decoding algorithm, can be used to approximate the channel capacity. Specifically, in a multi-user or multi-antenna system, a joint iterative detection decoding algorithm cascades MIMO detection and decoding together, and in the existing algorithm, the optimal detection part mostly uses list ball decoding. The detection algorithm preserves the soft information of the detection result of the list ball decoding algorithm by the MAP bit detection algorithm, and improves the detection performance. Take the MIMO multi-antenna system as an example (the same applies to multi-user systems). The system block diagram shown in Figure 1 includes the following steps:

Step 11: In the inner MIMO detector, the received signal is detected by using a ball decoding detection algorithm to obtain a candidate set list.

The candidate set list includes a plurality of selectable detection signal vectors, and each vector is composed of transmission symbols of each transmit antenna. In this step, the ball decoding detection algorithm is used to find a plurality of detection signal vectors that are closer to the real transmission symbol vector, and constitute a candidate set list, and the log likelihood ratio of each bit is calculated by the MAP bit detection algorithm.

Step 12: In the inner MIMO detector, using the candidate set list and the bit prior information OP60-090015 Calculates the output of information per bit.

In Turbo decoding, the out-of-bit information is the difference between the log-log likelihood ratio and its prior information, and is the new information obtained when calculating the log-likelihood ratio per bit.

Step 13. De-interleave the external information output by the inner MIMO detector and input it to the decoder.

Step 14: The deinterleaving result of the outer information obtained by using step 13 is input as a priori information of the outer soft-in soft-out decoder, and the decoded outer information result (including information bits and check bits) of all bits is output after decoding. ) and the log likelihood ratio of the information bits.

Step 15. If the maximum number of iterations is reached, the log likelihood ratio of the information bits output by the decoder is hard-decided to obtain the final desired information bit result, and the iterative detection decoding is ended. Otherwise, go to step 16.

Step 16. The external information outputted by the Turbo decoder is re-interleaved, and input as an a priori information to the detector for iterative detection, and the process proceeds to step 12.

In the iterative decoding algorithm performed in the above manner, although the soft information of the ball decoding can be preserved by the MAP bit detection algorithm, the system performance can be improved theoretically, but

The progress of the MAP bit detection algorithm depends on the determination of the candidate set list in step 11, so the computational complexity of the candidate set list is also affected by the performance of the entire joint iterative detection decoding algorithm. Specifically, the determining manner of the candidate set list in the step includes:

Step 11a, determining a sphere radius according to a channel estimation result;

Step lib, using a radius constraint to perform upper triangulation preprocessing on the channel matrix;

Step 11c: Searching for a possible transmitted symbol vector, that is, a symbol combination on all transmitting antennas, using a depth-first or breadth-first algorithm in a multi-dimensional hypersphere within a constrained radius with the received signal as the center of the sphere;

Step lid, if a reasonable solution is not found, increase the radius and search again; if a reasonable solution can be found, save it, and calculate a new radius based on the searched symbol combination. OP60-090015 Search again with the new radius until no better solution can be found;

Step lie, then the best value found is the optimal maximum likelihood solution.

The advantage of the above ball decoding algorithm is that it does not have to search all the lattice points in the entire lattice space, but only needs to search within a predetermined limited spherical area. Commonly used ball decoding algorithms are within a certain range of system parameters, such as the appropriate SNR interval, signal constellation size, number of transmitting and receiving antennas, and their complexity is polynomial, which is similar to the complexity of the linear detection method. However, due to the influence of the search radius and channel conditions, it is difficult to determine the number of grid points in the sphere with radius r, which results in the computational complexity of the ball decoding algorithm is uncertain. If the above parameters are not selected properly, the computational complexity of the algorithm is also exponential. Due to the diversity of actual channel types and signal-to-noise ratio conditions, it is difficult to optimize the design. It can be seen that this method cannot control resource allocation during hardware implementation, and often there is insufficient or waste of resources. Summary of the invention

In view of this, the present invention provides a joint iterative detection decoding method and apparatus, which can overcome the shortcomings of the ball decoding detection algorithm whose computational complexity is uncontrollable, and realize the detection result of the soft information with a small cost.

In order to achieve the above object, the present invention adopts the following technical solutions:

A joint iterative detection decoding method, comprising:

a. determining the number of optional constellation points corresponding to each transmitting antenna according to the number of detection signal vectors required for joint iterative detection, the modulation order M of the transmitting antenna, and the number of transmitting and receiving antennas, where c≤2 ^M , j is the transmit antenna index, and M is the modulation order of the transmit antenna;

b. According to the number of optional constellation points corresponding to each antenna determined in step a, among all the detection signal vectors, select f[detection signal vectors closest to the real transmission signal, OP60-090015 constitutes a candidate set list, where m is the number of transmit antennas, and the detected signal vector is a vector formed by any one of the constellation points of each transmit antenna;

c. Using the MAP bit detection method, the log likelihood ratio of each information bit is calculated according to all the detected signal vectors in the candidate set list.

A joint iterative detection decoding device includes: a storage unit, a detection signal vector selection unit, and a detection unit;

The storage unit is configured to save the number of optional constellation points corresponding to each transmitting antenna determined according to the number of detection signal vectors required for joint iterative detection, the modulation order M of the transmitting antenna, and the number of transmitting and receiving antennas. Where ≤ 2 ^M , j is the transmit antenna index, and M is the modulation order of the transmit antenna;

The detection signal vector selection unit is configured to select a distance true in a detection signal vector formed by a constellation point of each transmitting antenna according to the number of optional constellation points corresponding to each antenna stored in the storage unit. The most recent detection signal vector of the transmitted signal,

7=1

Forming a candidate set list, where m is the number of transmit antennas;

The detecting unit is configured to calculate a log likelihood ratio of each information bit according to all detection signal vectors in the candidate set list provided by the detection signal vector selecting unit by using a MAP bit detection mode.

As can be seen from the foregoing technical solutions, in the embodiment of the present invention, first, determine the number of optional constellation points corresponding to each transmitting antenna; then, perform rounding on the current channel matrix to obtain a matrix R and a matrix Q, and use the matrix Q to The received signal y is weighted to obtain a weighted received signal

Q ^T y ; Next, among all the detection signal vectors, the detection signal vector closest to the real transmission signal is selected to form a candidate set list; finally, the MAP bit detection is performed.

7=1

Algorithm, determining the logarithm of each information bit according to all detected signal vectors in the candidate set list OP60-090015 likelihood ratio. In the above manner, on one hand, the number of optional constellation points of each transmitting antenna is determined to control the computational complexity, and on the other hand, the detection signal vector that is closer to the real transmitting signal is selected for signal detection, thereby ensuring detection performance. . BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system block diagram of a conventional joint detection decoding.

Fig. 2 is a schematic diagram of searching for a detection signal in accordance with a tree structure.

FIG. 3 is a structural diagram of a joint detection and decoding apparatus according to an embodiment of the present invention.

4 is a schematic diagram showing simulation results of performance comparison between the method of the embodiment of the present invention and other existing detection methods. Mode for carrying out the invention

In order to make the objects, technical means and advantages of the present invention more comprehensible, the present invention will be further described in detail with reference to the accompanying drawings.

The basic idea of the embodiment of the present invention is: first determining the number of optional constellation points of each transmitting antenna, and then selecting a detection signal vector that is closer to the real transmission signal among all the constellation points, thereby limiting the number of detection signal vectors. At the same time, to ensure detection performance.

The detection method of the embodiment of the present invention is based on Hochwald's log-likelihood ratio calculation method based on the MAP bit detection algorithm. Next, the log likelihood ratio calculation method will be first introduced.

Consider a MIMO channel whose mathematical model is:

y = Hx + n ( 1 )

Where X is the transmitted symbol vector on the transmitting antenna, j is the received signal vector on the receiving antenna, and H is the transmission channel matrix, "is a Gaussian white noise vector. Let the bit vector formed by the signal to be detected be 6 , which is given by equation (2): OP60-090015 x _m =map(b ^<m> ),m = l,---,M (2)

Where 6 ^<m> is a data bit vector of Μ _ε x 1 dimension, Μ _ε is the number of bits contained in each constellation symbol, Μ is the number of transmitting antennas, ^ is the modulation of the bit vector ^<m> signal.

^"In the data bit M'M _e -J , let =1 denotes logic 1, b _k =_1 denotes logic 0, and the log likelihood ratio when the received signal is j is:

P[b _k =+11 J]

L _D (b _k \y) = \n (3)

P[b _k = -11 J]

Assume that after channel coding and interleaving, it can be considered statistically independent, then according to Bayes' theorem:

Where X _k , ₊₁ is a set of bit vectors 6 , and wherein ^ = +1, ie

Is a collection of serial numbers ';

J _kfi ={j\ j = 0,-,MM _c -l,j≠k,b _j =l} (6)

Multiply the numerator and denominator by _εχρ μ ₂ . χ^ - ¹ L _A (b _k ) Let equation (4) be:

Among them, 6^ is the sub-vector after the vector 6 removes the first element, and /^^ ₇ is the value after the log likelihood ratio L _{A is} removed. Therefore, L _D can be recorded as a priori information L _A and external information ^ OP60-090015

According to the above formula (8), in the structure shown in Fig. 1, the log likelihood ratio for the bit vector can be expressed as:

Ik]

(9)

1

L 4,W where L _£i =L _Di -L _Ai , which is the outer information of the bit vector, initially L _Ai =0, ie L _Ei =L _Di , which is the received signal of the inner MIMO detector in FIG. 1 : The detection result of V.

The information in formula (9) is:

^ indicates the coded bit to be transmitted, : V is the receive vector. Then equation (8) becomes the a posteriori log likelihood ratio obtained by the outer channel coding. Therefore, the external soft-in soft-out decoder in Figure 1 can be divided into a priori information and an external information, which can be obtained as follows:

L _D , (b, _k \L _A ) = L _A , b ₂ , _k ) + ( 11)

In equation (11), the result L is the log likelihood ratio L, L of all encoded bits (including information bits and parity bits) output by the outer soft-in soft-out decoder, which is the pair of output information bits. Number likelihood ratio.

Wherein, the uncoded data bits are recorded as Χ _λ , and + is the same vector set as the length of the interleaver OP60-090015

Using the Max-log approximation method, the outer information of equation (8) can be given by:

In the inner MIMO detector shown in FIG. 1, the received signal: V can be detected by applying the formula, and the outer information of the bit vector bl is obtained, that is, the operation of step 2 described in the background art. Where x = map (P ^ ₊₁ is all the detection signal vectors when b _k = +l in the candidate set list, and is all the detection signal vectors when = -1 in the candidate set list. The candidate set of the embodiment of the present invention is specifically The manner in which the detected signal vectors are determined in the list is described later.

For the external information output of the decoder, the BCJR algorithm is adopted as the decoding algorithm of the standard Turbo code of 3GPP. For the standard decoding algorithm, only the log likelihood ratio calculation of the system information bits and the corresponding external information output are performed, and in the iterative detection and decoding algorithm, the outer information output of all coded bits is required to be interleaved as the a priori information of the detector. Therefore, it is also necessary to calculate the external information of the check bits. The information out-of-information information L _E (ul ) and the log-likelihood ratio L _D (ul ) are calculated according to equations (13) and (14), respectively, that is, the operation of step 4 described in the background art.

L _D (u _k ^s ) = L _c x _k ^s + L(u _k ^s ) + L _E (u _k ^s ) (14)

The external information L _£ ( ) for the check digit is calculated according to equation (15) OP60-090015

Wherein, AW and AW are forward recursive and backward recursive metrics, respectively, and branch metrics of system information bits and check bits, respectively. Is the a priori information passed between the component decoders, L _£ = 4«E _s / N. Is the channel value. The MAX_LOG_MAP algorithm can be used to reduce the complexity of the algorithm.

The above theoretically derived formula is applied to the joint iterative detection decoding method described in the background art, that is, joint detection can be performed on the MIMO system. However, as described in the background art, in the joint iterative detection decoding method, the computational complexity is related to the number of detection signal vectors in the candidate set list, and in the current ball decoding detection, in the candidate set list The determination of the detection signal vector is not deterministic. Therefore, when the hardware implements the joint iterative detection decoding method described above, the resource allocation cannot be controlled, and the phenomenon of insufficient or wasted resources often occurs.

In the joint iterative detection and decoding method in the embodiment of the present invention, when determining the candidate set list, first determining the number of selectable constellation points corresponding to each transmit antenna, and then, in all the detected signal vectors, according to each transmit antenna The number of optional constellation points is selected, and the f[detection signal vectors closest to the real transmission signal are selected to form a candidate set list. Here, the test letter

7=1

The number vector is a vector formed by any one of the constellation points of each transmitting antenna. In this way, on the one hand, the total number of detection signal vectors in the candidate set list can be limited by the number of optional constellation points, thereby controlling the complexity of detection; on the other hand, when selecting the detection signal vector constituting the candidate set list, The distance of the real transmitted signal is standard, thus ensuring the detection performance.

Specifically, the implementation of the detection signal vector constituting the candidate set list among all the detection signal vectors may be implemented in various manners, for example, the most direct traversal manner. OP60-090015 In the present invention, in order to further reduce the computational complexity, according to the number of optional constellation points of each constellation point, the detection signal is searched according to the tree structure, and corresponding constellation points are selected for each transmitting antenna to form a candidate set list. Detection signal vector. Among them, by triangulating the channel matrix, the signal detection can be iterated from the last transmitting antenna, and the selection process of the detection signal vector can be simplified. In this process, the selection condition of the aforementioned detection signal vector is required (ie, the detection signal vector closest to the real transmission signal is selected)

7=1

Corresponding modifications are made. First, in the tree structure search mode, the selection conditions on which the detection signal vectors constituting the candidate set list are selected are derived.

QR decomposition of the /ixm-dimensional channel matrix H, H can be written as:

H = QQ' (16) where R is an upper triangular matrix of mxm dimensions, and the diagonal elements are integers, the Q ^j nxm 酉 matrix, and β ' is the 酉 matrix of x(/im). Known by formula (1)

(17)

According to formula (17)

The above formula can be recorded as

|/_Rx| =||« ( 18)

Where / = β ^Γ ν , ||n| ² =||n|| ² - [Q'Y y ² , if m = w, then ' = «. From the properties of the upper triangular matrix of R, equation (18) can be expanded to: -∑, ^r j,i ^x i , i = 1,2,'·' ,m ( 19)

It can be seen from equation (19) that only the constellation points on each transmitting antenna are selected. OP60-090015

The closer the detection signal vector formed by the ∑ point is to the real transmitted signal. Therefore, on the principle of 越 as small as possible, select each transmitting antenna.

The constellation points, the selected constellation points constitute a detection signal vector in the candidate set list, and are used to perform the MAP bit detection algorithm. In addition, since R is an upper triangular matrix, the magnitude of £ when j = m

Except for the matrix R and the signal y', it only depends on the value of the constellation point of the last transmitting antenna m, but has nothing to do with the value of the constellation points of other transmitting antennas; when j = ml, the size is divided by the matrix R In addition to the signal y', it only depends on the value of the constellation point of the last transmitting antenna m and the penultimate transmitting antenna m-1, and is independent of the value of the constellation points of other transmitting antennas; When = l, the size of I: depends on the matrix R and the signal y', and depends on the constellation point values of all transmit antennas. According to the above rule, when selecting a constellation point as a detection signal vector element for a transmitting antenna, the embodiment selects a constellation point for each transmitting antenna from the last transmitting antenna, and the selection basis is: before the current transmitting antenna Any combination of constellation points selected by the selected transmit antenna selects the constellation point that minimizes £ _; joins the candidate set

In the table, a detection signal vector is formed.

In a specific implementation, the embodiment of the present invention starts from the last transmitting antenna, selects constellation points for each transmitting antenna in turn, and forms at least one tree structure by using constellation points selected for all transmitting antennas, and selects the last transmitting antenna for the last transmitting antenna. The constellation point is the root node of the tree structure, the constellation points selected for other transmitting antennas are sequentially arranged as the sub-nodes of the root node, and the constellation points selected for the same transmitting antenna are located in the same layer of the tree structure; Root of structure The node of OP60-090015 is the last layer of the tree structure, and the layer where the leaf node is located is the first layer of the tree structure; the number of tree structures finally formed is equal to the number of constellation points selected by the last antenna. In all the tree structures formed, all constellation points included in the path from each leaf node to the root node serve as a detection signal vector in the candidate set list.

Specifically, a constellation point selected for the last transmit antenna is used as a root node; when a j-th layer is formed by selecting a constellation point for the jth transmit antenna, each of the nodes of the j+1th layer One, select the _Cj constellation points that make y'j - ∑ ^r j,i ^x i the smallest as the child nodes of the current node of the j+i layer. Until the constellation points are selected for all transmit antennas to form a complete tree, the complete tree is: the path from all leaf nodes to the root node of the tree includes m nodes, and m is the number of transmit antennas.

The QPSK modulation mode is taken as an example. The number of all constellation points of each transmitting antenna is 4, and the predetermined optional constellation points are: the optional constellation corresponding to the 1st and 2nd transmitting antennas. The number of points is one, and the number of optional constellation points corresponding to the third and fourth transmitting antennas is four, as shown in FIG. 2 .

First, starting from the 4th transmit antenna, select 4 constellation points as the root node, as shown in the root layer of Figure 2, node 1, node 2, node 3, and node 4; then, select the constellation for the third transmit antenna. Point, for node 1 of layer 4 (ie, the root layer), select 4 constellation points for the 3rd transmit antenna to form the 3rd layer of the tree structure, and place the 4 constellation points (node 5 in Figure 2) , node 6, node 7 and node 8) as the child nodes of node 1, and the other nodes of the fourth layer also select the constellation points of the third transmitting antenna in the above manner; next, select the constellation points for the second transmitting antenna For node 5 of layer 3, select one constellation point that minimizes the value of £ - ί _{2 Λ} ² for the second transmit antenna (node 9 in Figure 2)

j=2 1=2 '

As a child node of the node 5, the other nodes of the third layer are also selected as the second method as described above. OP60-090015 The constellation point of the root transmitting antenna; similarly, the constellation point is selected for the first transmitting antenna, and the selected constellation point is used as the child node of the layer 2 node, and finally constitutes 4 complete trees, respectively, tree A , tree tree C and tree D. So far, all the constellation points included in the path from the leaf node to the corresponding root node constitute a detection signal vector in the candidate set list, and the four trees include a total of 16 detection signal vectors. Since the constellation points which minimize y are selected each time during the selection process, the detection signal vector formed by the above method is

A set of constellation points that make i smaller, thus ensuring detection

•6匕

Next, a specific implementation manner of the embodiment of the present invention is described in detail by searching for and selecting a detection signal vector by using a tree structure, wherein when the constellation point selection of the transmitting antenna is performed according to the above tree structure, the breadth-first search may be performed. In the mode, when the constellation point is selected for the jth antenna, all the nodes for the j+1 layer are selected, and then selected for the subsequent transmit antenna; or, the depth-first search mode may be performed, that is, When the j-th antenna selects the constellation point, after selecting one node of the j+1 layer, the selection of the subsequent transmit antenna is started, and after the selection of a detection signal vector is completed, the root node or other child nodes are returned. Select the subordinate node for the remaining root node or other child nodes.

The following embodiment is described by taking the breadth-first search method as an example.

Step 21: Determine the number of optional constellation points corresponding to each transmitting antenna.

In this step, for each transmit antenna, the number of selectable constellation points that can be used as the detected signal vector in the candidate set list is determined from all constellation points of the transmit antenna.

Basically, the number of optional constellation points corresponding to each transmitting antenna may be determined according to the number of detection signal vectors required for joint iteration detection, the modulation order of the transmitting antenna, and the number of transmitting and receiving antennas. For example, in a MIMO system with 4 receivers and 4 receivers, the transmit antenna uses QPSK tuning. In the OP60-090015 system, the number of detection signals required for joint iterative detection is 16, then the modulation order of the transmitting antenna is 2, and the constellation points corresponding to the transmitting antenna are 4, then 4 transmitting antennas can be selected correspondingly. 1, 4, 4 constellation points, so that the detection signal vector formed by these constellation points can have 1x1x4x4 = 16. For the sake of computational complexity, if the number of transmitting antennas is small, the modulation order is lower, and a larger one can be selected. If the modulation order is higher and the number of transmitting antennas is larger, if it is large, it will cause The computational complexity is unbearable, so there are not many options that are large.

Generally, the higher the energy of the transmitting antenna, the higher the detection accuracy of the transmitting signal on the receiving end; the lower the energy of the transmitting antenna, the lower the detection accuracy of the transmitting signal on the receiving end, therefore, For a high-energy transmitting antenna, fewer optional constellation points can be selected, that is, the detection performance can be ensured; for a low-energy transmitting antenna, more optional constellation points need to be selected to ensure detection performance. Based on the above considerations, in order to further ensure the detection performance, in addition to determining the number of optional constellation points corresponding to each transmitting antenna according to the foregoing factors, the energy of each transmitting antenna may be further performed. Specifically, the energy of each transmitting antenna is calculated according to the channel matrix in advance. When determining the number of optional constellation points, a larger number of selected points is selected on the antenna with lower energy, and a smaller selection is selected on the antenna with higher energy. By counting the number, a set of detection signal vectors closer to the real transmission signal can be searched, and the external information L _£ ( IJ) is calculated based on the signal set.

Step 22: Perform upper triangulation on the current channel matrix to obtain a matrix R and a unitary matrix Q, and use the transposed Q ^T of the unitary matrix Q to weight the current received signal y to obtain a weighted received signal y '

= Q ^T y.

Step 23: Calculate each of all constellation points corresponding to the last transmit antenna

I -^ Λ| ² , Select the smallest _Cm constellation points in all I - Λ| ² obtained, and use each constellation point as the root node of a tree. OP60-090015 Step 24. Use the last transmit antenna of the last transmit antenna as the current transmit antenna j.

Step 25: For each of the nodes of the j+1th layer in all the tree structures, select the smallest constellation point as the child node of the current node of the j+1th layer, where the value has been determined, and Since the search process starts from the root node, before the step, the j+1th layer to the root node are known, that is, ... ^ is known, and for each node of the j+1th layer, the current is transmitted. All constellation points of the antenna; ^ selects the constellation points that make the norm y the smallest as the child nodes of the current node of the j+i layer. among them,

x _j+1 ...^ is all constellation points included in the path from the current node to the root node.

Since the breadth-first search method is adopted in this embodiment, this step selects a constellation point for each node of the j-th layer of all tree structures, as shown in FIG. 2, if j=2, The 16th layer 3 nodes respectively select a constellation point, thereby realizing the constellation point selection for the current transmitting antenna.

Step 26: Determine whether the current transmitting antenna is the first transmitting antenna. If yes, all the constellation points included in the path from the leaf node to the corresponding root node form a detection signal vector, join the candidate set list, and perform step 27 Otherwise, the next transmit antenna of the current transmit antenna is taken as the current transmit antenna j, and the process returns to step 25.

The above steps 23 to 26 are processes for determining the candidate set list by means of breadth-first search. The number of detection signal vectors in the candidate set list determined by the above manner can reach a preset level, and the detection performance can be guaranteed.

Step 27: Determine a log likelihood ratio of information bits on all transmit antennas by using all detected signal vectors in the candidate set list.

The operation of this step can be performed by the operations of steps 12 to 16 described in the background art. OP60-090015 is completed, so I will not repeat them here.

So far, the joint iterative decoding detection method of the embodiment of the present invention ends.

In fact, the detection signal vector in the candidate set list can also be determined by depth-first search. Specifically, in steps 23 to 26, as shown in FIG. 2, each time the constellation point of the current transmitting antenna is determined, only for the current A node of the jth layer in the tree selects a constellation point until a constellation point of the first transmitting antenna is determined; then, returns to the jth layer, selects a constellation point for the other leaf nodes, and so on, until the construct The complete 4 trees shown in Figure 2.

When the number of optional constellation points is determined in step 21 of the above embodiment, the number of optional constellation points is determined in real time according to each parameter. In fact, in order to simplify the processing, it is also possible to pre-assign the corresponding number of optional constellation points for each transmitting antenna according to a predetermined combination of the number of optional constellation points in the signal detection. In this way, the number of optional constellation points can be set in advance in the hardware device, and the corresponding constellation points can be directly allocated according to the set of optional constellation points in real time during signal detection. For example, taking four transmitting antennas as an example, the number of optional constellation points of all transmitting antennas may be determined in advance as follows: The number of optional constellation points corresponding to four transmitting antennas with high to low energy is 1, 1, 4, respectively. 4; then, at the time of signal detection, determining the energy of each transmitting antenna, and then assigning corresponding number of constellation points to the corresponding transmitting antenna according to the energy, that is, the highest and the second highest energy transmitting antennas are allocated. The number of optional constellation points is 1, and the number of optional constellation points allocated to the second and lowest energy transmitting antennas is 4.

More specifically, when implementing the foregoing manner, preferably, an optional constellation point combination may be set in the hardware device, and when performing signal detection, determining the energy of each transmitting antenna according to the channel matrix, and following the order of energy from high to low Rearranging the columns, the transmitting antennas, and the received signals in the channel matrix, and using the rearranged channel matrix as the current channel matrix, and sorting the connections OP60-090015 Receive signal as the current received signal y, then perform steps 22 ~ 26, and when transmitting steps 23 ~ 26, the transmitting antennas are all arranged in the sorted order. After performing step 26, further, the elements in each detection signal vector in the candidate set list are rearranged according to the order of the transmitting antennas before sorting, and then step 27 is performed, and all the rearranged detection signal vectors are used to determine all The log likelihood ratio of the information bits on the transmit antenna. By adding rearrangement operations, the complexity of the entire process is reduced.

In the above embodiment, when a constellation point is selected for each transmitting antenna, the value of _Cj ranges from 1 ≤ ^ ≤ 2 ^Μ , and M is the modulation order of the transmitting antenna. If = 2 ^Μ , that is, all the constellation points of the corresponding layer under each node of the + i layer are selected, so that the calculation of ( 19 ) is not required, thereby greatly reducing the calculation amount.

If _c = ι, that is, only one constellation point is selected under each node of the +i layer as the first node under the + i layer node, then the formula y) is expanded to obtain:

The nearest constellation points of the ministry and the imaginary part. Therefore, if ^ = 1 , only r, . , . , and then the real and imaginary parts are respectively compared with the real and imaginary parts of all constellation symbols of the current transmitting antenna, respectively, the real part and the imaginary part are respectively the nearest The point is the constellation point that makes y the smallest. OP60-090015 It can be seen from the above that the calculation amount is greatly reduced when . = 1 or = 2 ^M , so the embodiment of the present invention suggests that for the selection, under the premise of the same number of detection signal vectors, it is taken as 2^ as much as possible. Or 1 is appropriate to reduce the amount of calculation, which is a simplified tree search detection method.

The embodiment of the invention further provides a joint iterative detection and decoding device, and the specific structure is as shown in the figure

3 is shown. The apparatus includes a storage unit, a detection signal vector selection unit, and a detection unit. Specifically, the storage unit is configured to save the number of optional constellation points corresponding to each transmitting antenna determined according to the number of detection signal vectors required for joint iterative detection, the modulation order M of the transmitting antenna, and the number of transmitting and receiving antennas. Where ≤ 2 ^M , j is the transmit antenna index, M is the modulation order of the transmit antenna; the detection signal vector selection unit is configured to use the number of selectable constellation points corresponding to each antenna stored in the storage unit, In the detection signal vector composed of one constellation point of each transmitting antenna, selecting the nearest detection signal from the real transmitting signal

7=1

a vector, constituting a candidate set list, where m is a number of transmit antennas; a detecting unit, configured to calculate, by using a MAP bit detection manner, a pair of each information bit according to all detected signal vectors in the candidate set list provided by the detection signal vector selecting unit Number likelihood ratio.

In the tree structure search selection detection signal vector as an example, a specific structure of the detection signal vector selection unit is provided, including a weighting unit and a constellation point selection unit. Specifically, the weighting unit is configured to perform upper triangulation processing on the current channel matrix to obtain a matrix R and a unitary matrix Q, and weight the current received signal y by using the conjugate transposed Q ^T of the unitary matrix Q to obtain a weighted received signal y' = The Q ^T y ; constellation point selection unit is configured to select constellation points for all the transmitting antennas by using a tree search method according to the number of optional constellation points corresponding to each transmitting antenna in the saving unit and the weighted receiving signals provided by the weighting unit. A detection signal vector in the candidate set list is formed.

Specifically, the memory cell and the detection signal vector selection unit in the above apparatus may be in FIG. The OP60-090015 is implemented in an internal MIMO detector in the system, and the detecting unit can be implemented by using the WAP bit detection method of the system shown in FIG.

According to the joint iterative detection decoding method and apparatus according to the above embodiments of the present invention, no radius constraint is required for performing the search of the detected signal vector (a typical ball decoding algorithm requires a radius constraint); an optional corresponding to each transmitting antenna may be adopted. Controlling the number of constellation points to control the number of detection signal vectors, thereby controlling the computational complexity; meanwhile, when selecting the detection signal vector, selecting the detection signal vector that is closer to the real transmission signal, and then using these selected detections The signal vector performs signal detection to ensure detection performance.

Further, in the method and apparatus for searching for the selection detection signal vector based on the tree structure given in the above embodiment, the search process of each constellation point in the detection signal vector can be calculated in parallel, the algorithm complexity is fixed, and the hardware design is easy. And the implementation; the simplified tree search detection algorithm has low complexity, and the complexity is not sensitive to the increase of the antenna or the number of multi-users; the bit log likelihood ratio soft information can be output in parallel, and the hard decision result can also be output; the detector can be utilized An iterative detection decoding algorithm for external information transfer between decoders improves performance.

The simulation results of the method of applying the embodiment of the present invention are given below. Considering the 4x4 MIMO system, the candidate set including 256 detection signal vectors is adopted, and the combination of the selection points is taken as C = [l; l; 16; 16]. The system simulation conditions are shown in Table 1, and the simulation results are shown in Fig. 4. .

Table 1 Simulation condition settings

OP60-090015

In Fig. 3, curve 1 (ZF) is expressed as the simulation performance of the zero-forcing detection method, curve 2 (ZFLLR) is the simulation performance of the zero-forcing weighted detection method, and curve 3 (MMSE) is expressed as the simulation performance of the minimum mean square error detection method. Curve 4 (RTSD (Reduced Tree Searching Detection) hard decision result) and curve 5 (RTSD soft decision result) represent simulation performance of the simplified tree search detection method in the embodiment of the present invention, and curve 6 UIDD, Jointed Iterative Detection & Decoding) The simulation performance of the joint iterative detection decoding method of the embodiment of the invention has an iteration number of 1.

It can be seen from the simulation results that the BER curve of the simplified tree search detection method is faster than that of the zero-forcing and zero-forcing detection algorithm, and when the BER is close to 10, the simplified tree search detection algorithm has a hard decision result than the ZFLLR detection algorithm. well 9dB above, about 3dB better than the MMSE, and the soft decision results in BER close above ^10-4 Shi 1.5dB better than the hard decision result. The joint iterative detection decoding algorithm with one iteration has the best performance, and the soft decision result is about 0.8dB. It can be seen that the performance of the simplified tree search detection algorithm is significantly improved compared with the linear algorithm, and is convenient for hardware design and implementation. It is a very effective detection algorithm, and the performance is obtained after joint iterative detection and decoding algorithm based on simplified tree search detection. Can be further improved.

The above are only the preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and scope of the present invention are intended to be included within the scope of the present invention.

Claims

OP60-090015 Claim

A joint iterative detection decoding method, characterized in that the method comprises:

b. According to the number of optional constellation points corresponding to each antenna determined in step a, among all the detection signal vectors, select f[detection signal vectors closest to the real transmission signal,

7=1

Forming a candidate set list, where m is the number of transmit antennas, and the detected signal vector is a vector formed by any one of the constellation points of each transmit antenna;

2. The method according to claim 1, wherein the step b comprises: bl, performing an up-triangulation process on the current channel matrix to obtain a matrix R and a unitary matrix Q, and using a conjugate transpose Q of the unitary matrix Q ^T weights the current received signal y to obtain a weighted received signal y' = Q ^T y ;

B2: Selecting constellation points for all transmitting antennas in a tree search manner according to the number of optional constellation points corresponding to each transmitting antenna and the weighted receiving signal, and forming a detection signal vector in the candidate set list.

3. The method according to claim 2, wherein the constellation points are selected for other current transmitting antennas other than the last transmitting antenna: corresponding to each combination of {w, . . . , _m }, Select the smallest constellation point, where j is the current launch day

The number of the line, m is the number of transmitting antennas, which corresponds to the current transmitting antenna in the weighted received signal. The component of OP60-090015 is the element of the first column of the jth row of the matrix R, ₊ ,..., which is the constellation point selected by the j+1th transmit antenna to the mth transmit antenna, respectively, · is the current transmit antenna Any one of the constellation points is the number of optional constellation points corresponding to the jth transmit antenna determined in step a.

4. The method of claim 2, wherein selecting the constellation points is a last transmitting antenna way: any transmission antenna corresponds to the last one of all the ^M 2 constellation points in a _m, Calculation I - Γ _μ , _λ | ² , the smallest _Cm constellation points are selected as the constellation points selected by the last transmit antenna among all the values of I - Γ _μ , _λ | ² .

The method according to claim 2, wherein in step c, a constellation point is selected for all transmit antennas according to a depth or breadth priority search.

6. The method according to claim 1, wherein the number of selectable constellation points corresponding to each of the transmitting antennas is further determined according to the energy of each of the transmitting antennas determined by the channel matrix.

7. The method according to claim 6, wherein the lower the energy, the larger the number of optional constellation points corresponding to the transmitting antenna, and the smaller the energy, the smaller the number of optional constellation points corresponding to the transmitting antenna.

The method according to claim 1, wherein the determining the number of optional constellation points corresponding to each of the transmitting antennas comprises:

Determining, according to the number of detection signal vectors required by joint iterative detection, the modulation order of the transmitting antenna, and the number of transmitting and receiving antennas, determining the number of optional constellation points of all transmitting antennas;

When performing signal detection, each of the transmitting antennas is arbitrarily assigned a corresponding number of optional constellation points according to a predetermined combination of the number of optional constellation points.

9. The method according to claim 1, wherein said determining each transmission OP60-090015 The number of optional constellation points corresponding to the antenna includes:

When performing signal detection, according to a predetermined combination of the number of optional constellation points, each of the transmitting antennas is allocated a corresponding number of optional constellation points according to the energy of each transmitting antenna determined by the channel matrix, and the lower the energy The larger the number of optional constellation points corresponding to the transmitting antenna, the smaller the number of optional constellation points corresponding to the transmitting antenna with higher energy.

10. The method of claim 9 wherein:

Before step a, the method further includes: determining, according to the channel matrix, energy of each of the transmitting antennas, and rearranging the columns, the transmitting antennas, and the received signals in the channel matrix according to the order of high to low energy, and rearranging the rearranged channels. The matrix is used as the current channel matrix, and the sorted received signal is taken as the current received signal y;

The transmitting antennas in step c are transmitting antennas arranged in the sorted order;

Further comprising, between steps c and d: rearranging elements in each of the detected signal vectors in the candidate set list according to the order of the transmitting antennas before the sorting;

The detection signal vector in step d is the rearranged detection signal vector.

The method according to claim 1, wherein the number of optional constellation points corresponding to each of the transmitting antennas determined in step a is 1 or 2 ^M.

The method according to claim 3 or 4, wherein if the number of optional constellation points corresponding to the jth transmitting antenna j is 1, then selecting y) - ∑, ^r j, i ^x i is the smallest _; the constellation points comprises: count - the calculation result of the real part and the imaginary part of

Comparing the real and imaginary parts of each constellation point of the jth transmitting antenna, selecting a distance OP60-090015,

y) ~ the nearest constellation point;

If the number of optional constellation points corresponding to the jth transmit antenna is 2 ^M , then the smallest constellation point is selected as: Select all the constellations of the jth transmit antenna

*.

13. A joint iterative detection decoding apparatus, the apparatus comprising: a storage unit, a detection signal vector selection unit, and a detection unit;

7=1

Forming a candidate set list, where m is the number of transmit antennas;

14. The apparatus according to claim 13, wherein the detection signal vector selection unit comprises a weighting unit and a constellation point selection unit;

The weighting unit is configured to perform an up-triangulation process on the current channel matrix to obtain a matrix R and a unitary matrix Q, and weight the current received signal y by using a conjugate transposed Q ^T of the unitary matrix Q to obtain a weighted received signal y' = Q ^T y ; OP60-090015, the constellation point selecting unit, configured to perform all the transmissions by a tree search method according to the number of optional constellation points corresponding to each transmitting antenna in the saving unit and the weighted receiving signal provided by the weighting unit The antenna selects the constellation points to form a detection signal vector in the candidate set list.