CN115396064A - Detection decoding method and device, computer equipment and readable storage medium - Google Patents
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Abstract
The application relates to a detection decoding method, a detection decoding device, computer equipment and a readable storage medium. The method comprises the following steps: the method comprises the steps of determining symbol vectors of all channels based on input bits received by a communication system and channel matrixes corresponding to all channels of the communication system, obtaining a plurality of synchronous sets corresponding to the input bits according to the symbol vectors of all the channels, carrying out decoding search on all the synchronous sets to obtain a target path, and determining a target detection decoding result according to the target path and a target detection decoding function. By adopting the method, decoding search can be carried out based on the obtained multiple synchronous sets, and decoding search does not need to be directly carried out on input bits, so that the decoding search times can be reduced, the complexity of a decoding detection processing process is reduced, the accuracy of a decoding detection result is improved, and the error correction performance of the MIMO system is further improved.
Description
Technical Field
The present application relates to the field of wireless communication technologies, and in particular, to a detection and decoding method, apparatus, computer device, and readable storage medium.
Background
With the rapid development of the information society, mobile communication data is exponentially increased, and the communication quality required for the mobile communication data is also increasingly high. In order to improve communication quality, it is common to increase channel capacity in a communication system, such as a nonlinear (MIMO) system.
In the working process of the MIMO system, a transmitting end of the MIMO system mainly transmits signals to a receiving end, and the receiving end correctly recovers the multi-path transmitting signals corresponding to the transmitting end, wherein two processing processes, namely signal detection and decoding processing, are included in the signal transmission and receiving processes. However, the implementation of signal detection and decoding processes using the related art may result in poor error correction performance of the MIMO system.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a detection and decoding method, device, computer device and readable storage medium capable of improving error correction performance of a MIMO system.
In a first aspect, the present application provides a detection decoding method, including:
determining a symbol vector of each channel based on input bits received by a communication system and a channel matrix corresponding to each channel of the communication system;
acquiring a plurality of synchronous sets corresponding to input bits according to the symbol vectors of all channels; the synchronous set is a set formed by combining input bits;
decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances corresponding to the detection decoding;
and determining a target detection decoding result according to the target path and the target detection decoding function.
In one embodiment, obtaining a plurality of synchronization sets corresponding to input bits according to a symbol vector of each channel includes:
determining Euclidean distance increment corresponding to each symbol vector according to the equivalent receiving vector and the symbol vector of each channel;
and obtaining a plurality of synchronous sets according to the Euclidean distance increment corresponding to each symbol vector.
In one embodiment, before determining the euclidean distance increment corresponding to each symbol vector according to the equivalent received vector and the symbol vector of each channel, the method further includes:
and determining the equivalent receiving vector of each channel according to the symbol vector, the target noise vector and the triangular matrix of each channel.
In one embodiment, obtaining a plurality of synchronization sets according to the euclidean distance increment corresponding to each symbol vector includes:
acquiring the determining time of Euclidean distance increment corresponding to each symbol vector;
and respectively determining the Euclidean distance increments with the same determination time as a plurality of corresponding synchronous sets.
In one embodiment, decoding and searching each synchronization set to obtain a target path includes:
determining a preset search threshold value of decoding search based on a multi-tree search strategy;
establishing a search tree based on each synchronous set;
according to a preset sequence in the search tree, determining an adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree according to the input bits corresponding to each level in the search tree;
selecting a path meeting the target search condition from the search tree and determining the path as a target path; the target search condition is a path with adjacent Euclidean distances between any two adjacent input bits in any two adjacent levels in the search tree smaller than a preset search threshold value, and the path comprises a plurality of input bits.
In one embodiment, determining the target detection decoding result according to the target path and the target detection decoding function includes:
and substituting the sum of all adjacent Euclidean distances corresponding to the target path into a target detection decoding function to obtain a target detection decoding result.
In one embodiment, before determining the target detection decoding result according to the target path and the target detection decoding function, the method further includes:
and obtaining a target detection decoding function according to the equivalent receiving vector and the symbol vector of each channel.
In one embodiment, determining a symbol vector for each channel based on input bits received by the communication system and a channel matrix corresponding to each channel of the communication system comprises:
performing orthogonal triangular decomposition on a channel matrix corresponding to each channel to obtain a triangular matrix;
and modulating the input bits according to the triangular matrix and the polarization matrix to obtain a symbol vector of each channel.
In a second aspect, the present application further provides a detection decoding apparatus, including:
a symbol vector determining module, configured to determine a symbol vector of each channel according to an input bit received by a communication system and a channel matrix corresponding to each channel of the communication system;
a synchronous set module, configured to obtain multiple synchronous sets corresponding to input bits according to the symbol vector of each channel; the synchronous set is a set formed by combining input bits;
the decoding search module is used for carrying out decoding search on each synchronous set to obtain a target path; the target path is the path with the minimum Euclidean distance in the detection decoding;
and the detection decoding result determining module is used for determining a target detection decoding result according to the target path and the target detection decoding function.
In a third aspect, the present application further provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method in any one of the embodiments of the first aspect when executing the computer program.
In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the steps of the method of any of the embodiments of the first aspect.
The detection decoding method, the detection decoding device, the computer equipment and the readable storage medium are provided. The method comprises the steps of determining symbol vectors of all channels based on input bits received by a communication system and channel matrixes corresponding to all channels of the communication system, obtaining a plurality of synchronous sets corresponding to the input bits according to the symbol vectors of all the channels, carrying out decoding search on all the synchronous sets to obtain a target path, and determining a target detection decoding result according to the target path and a target detection decoding function; the method can perform decoding search based on the acquired multiple synchronous sets without directly performing decoding search on input bits, thereby reducing the decoding search times, reducing the complexity of a decoding detection processing process, improving the accuracy of a decoding detection result and further improving the error correction performance of the MIMO system; meanwhile, the method can also improve the speed of detecting and decoding, obtain the detection and decoding result in time and reduce the time delay of obtaining the detection and decoding result.
Drawings
FIG. 1 is a diagram of an exemplary embodiment of a detection decoding method;
FIG. 2 is a flowchart illustrating a method for detecting decoding according to an embodiment;
FIG. 3 is a flowchart illustrating a method for detecting decoding according to another embodiment;
FIG. 4 is a flowchart illustrating a method for detecting decoding according to another embodiment;
FIG. 5 is a schematic diagram of a process for generating a synchronization set in one embodiment;
FIG. 6 is a flowchart illustrating a method for detecting decoding according to another embodiment;
FIG. 7 is a block diagram of a search tree built in one embodiment;
FIG. 8 is a block diagram of an apparatus for detection decoding in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
The detection decoding method provided by the application can be applied to the computer equipment shown in FIG. 1. The computer device may be implemented as an independent server or a server cluster composed of a plurality of servers, and may also be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices.
The embodiment of the application provides a detection decoding method, and fig. 2 is a schematic flow chart of the detection decoding method. The method can realize a joint detection decoding process, reduce the complexity of a spherical decoding algorithm, has a simple processing process, can improve the detection decoding speed, can also reduce the detection decoding time delay of the MIMO system under the condition of aiming at low code rate, and can also improve the accuracy of the detection decoding result on the premise of simple processing process, thereby improving the error correction performance of the MIMO system. The following embodiment explains the detecting and decoding method by taking the computer device in fig. 1 as an example, and the detecting and decoding method may include the following steps:
s100, determining a symbol vector of each channel based on input bits received by the communication system and a channel matrix corresponding to each channel of the communication system.
The communication system may be a wired communication system or a wireless communication system, but in the embodiments of the present application, the communication system is described as an example of a wireless communication system. In one embodiment, the communication system is a MIMO system.
In one embodiment, the signal received by the receiving end of the communication system, i.e. the input bits, may be represented as u = [ u ]) 1 ,u 2 ,…,u N ]N denotes the total number of input bits, the channel matrix corresponding to each channel of the communication system
N t Representing the number of transmit antennas, N, of a MIMO system r Indicates the number of receive antennas of the MIMO system,
representing a complex field. In the embodiment of the present application, a MIMO system is taken as an uplink flat fading MIMO system as an example for description.
For example, the symbol vector s of each channel is determined based on the input bits received by the communication system and the channel matrix corresponding to each channel of the communication system, and may be an algorithm model trained in advance, and the input bits received by the communication system and the channel matrix corresponding to each channel of the communication system are all input into the algorithm model, and the symbol vector of each channel is output through the algorithm model.
It should be noted here that the channel of the MIMO system can be divided into two parts, i.e. reliable channel and unreliable channel, and the polarization code of the channel
N represents the total number of input bits, where K information bits are placed in the K most reliable channels for transmission, and N-K frozen bits (set to a fixed value, typically 0) are placed in the remaining N-K unreliable channels for transmission, i.e., the input bits include both information bits and frozen bits. Wherein the set of information bits transmitted by the reliable channel is represented as
The frozen bit set for unreliable channel transmission is represented as
In an embodiment, as shown in fig. 3, the step of determining a symbol vector of each channel in S100 based on the input bits received by the communication system and the channel matrix corresponding to each channel of the communication system may include:
and S110, performing orthogonal triangular decomposition on the channel matrix corresponding to each channel to obtain a triangular matrix.
It should be noted that a channel matrix corresponding to each channel may be used
An upper triangular matrix R obtained by performing orthogonal triangular decomposition (QR decomposition) i I.e. a triangular matrix, i denotes the ith channel.
And S120, modulating the input bits according to the triangular matrix and the polarization matrix to obtain the symbol vector of each channel.
Based on the obtained triangular matrix R i Can be based on a triangular matrix R i And a polarization matrix G N The input bit u is modulated to obtain a symbol vector s of each channel, i.e., s = MAP { x } = MAP { uB = N G N }。
Where x represents a code word (constructed by a polar code), B N Indicating a bit-flipping permutation and,
f is
N times the Kronecker product (i.e., kronecker product), n being equal to log 2 N, s is equal to(s) 1 ，...，s i )。
In the actual processing process, the symbol complex vector transmitted by the MIMO system
The symbol complex vector is received by the MIMO system through M-order quadrature amplitude modulation obtained by the polarization code
Can be expressed as
Wherein the content of the first and second substances,
is a channel matrix, in this embodiment, the H is a gaussian channel matrix with independent co-distribution,
representing the variance σ 2 Independent and equally distributed circularly symmetric white Gaussian noise. Carrying out real-value decomposition on the symbol complex vector to obtain an equivalent model y = Hs + N, wherein y and N are both lengths of 2N r A real vector of (2), H represents 2N t ×2N r A real matrix of (a).
Where the equivalent modulation process can be denoted as s i ＝map(x m(i-1)+1 ,…,x mi ) One real symbol corresponds to
Bits, so the vector output form of the map (-) function can be expressed as
MAP(x)＝[map(x 1 ,…,x m ),…,map(x N-m+1 ,…,x N )] T (1)。
And S200, acquiring a plurality of synchronous sets corresponding to input bits according to the symbol vectors of the channels. The synchronization set is a set obtained by combining input bits.
In particular, the above-mentioned synchronization set may be expressed as
j is less than N. For example, the plurality of synchronization sets corresponding to the input bits may be obtained by searching for a symbol vector equal to the symbol vector of each channel in the mapping relationship between the symbol vector and the synchronization sets, and using the synchronization set corresponding to the searched symbol vector as the plurality of synchronization sets corresponding to the input bits.
S300, decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances in the detection decoding.
Based on the synchronous set obtained in the above steps, a tree structure may be established first, and then each tree node may be traversed in the tree structure along a plurality of preset paths by using a search algorithm until a tail node is traversed, and a target path may be determined from the plurality of preset paths. The tree structure includes a plurality of tree nodes, and each tree node may be information in each synchronization set.
For example, if a predetermined path in the tree structure is a-B-C, after traversing the tail node C, the sum of the euclidean distances corresponding to the detection decoding may be equal to the sum of the euclidean distance between the tree node a and the tree node B and the euclidean distance between the tree node B and the tree node C.
S400, determining a target detection decoding result according to the target path and the target detection decoding function.
A certain percentage of the sum of Euclidean distances corresponding to the target path can be taken, and then the result of taking the percentage is substituted into a target detection decoding function to obtain a target detection decoding result. Or, the sum of the euclidean distances corresponding to the target path may be compared with the corresponding preset search threshold, and then the target detection decoding result may be obtained according to the comparison result and the target detection decoding function. Alternatively, the target detection decoding function may represent a corresponding optimization function in the detection decoding process.
The detection decoding method provided by the embodiment of the application can determine the symbol vector of each channel based on the input bit received by the communication system and the channel matrix corresponding to each channel of the communication system, acquire a plurality of synchronous sets corresponding to the input bit according to the symbol vector of each channel, perform decoding search on each synchronous set to obtain a target path, and determine a target detection decoding result according to the target path and a target detection decoding function; the method can perform decoding search based on the acquired multiple synchronous sets without directly performing decoding search on input bits, thereby reducing the decoding search times, reducing the complexity of a decoding detection processing process, improving the accuracy of a decoding detection result and further improving the error correction performance of the MIMO system; meanwhile, the method can also improve the speed of detecting and decoding, obtain the detection and decoding result in time and reduce the time delay of obtaining the detection and decoding result.
Next, a process of acquiring a plurality of synchronization sets corresponding to input bits based on the symbol vector of each channel in S200 will be described. In an embodiment, as shown in fig. 4, the step in S200 may include:
s210, determining Euclidean distance increment corresponding to each symbol vector according to the equivalent receiving vector and the symbol vector of each channel.
It can be understood that the equivalent receiving vector z and the symbol vector s of each channel may be processed to obtain the euclidean distance increment e corresponding to each symbol vector i 。
Before the step S210 is executed, the method may further include: and determining the equivalent receiving vector of each channel according to the symbol vector, the target noise vector and the triangular matrix of each channel.
The target noise vector may be a self-defined uniformly distributed noise vector, an exponentially distributed noise vector, a gamma noise vector, and the like, and in this embodiment, the target noise vector is an additive white gaussian noise vector.
In the embodiment of the present application, the MIMO system has a joint detection decoding model, and the joint detection decoding model is used to implement a detection decoding process. In one embodiment, if the joint detection decoding model shares a common equivalent channel N c ＝N/(M c N t ) N is c May be equal to 1,.. Times.i, and the equivalent receive vector z for each channel may be equal to
In the formula (2), the reaction mixture is,
is the Nth c The symbol vectors of the individual channels are,
is the Nth c The equivalent received vector for each of the channels,
is the Nth c An additive white gaussian noise vector for each channel,
is the Nth c A triangular matrix of individual channels.
Before the step of determining the target detection decoding result according to the target path and the target detection decoding function is executed, the method may further obtain the target detection decoding function according to the equivalent receiving vector and the symbol vector of each channel.
In order to improve the error correction performance of the MIMO system on the premise of reducing the complexity of the detection and decoding algorithm, the maximum likelihood detection algorithm may be used to implement the detection and decoding process, so in practical applications, the MIMO system maximum likelihood detection problem may be converted into a joint Maximum Likelihood (ML) detection and decoding problem, that is, a target detection and decoding function:
in equation (3), the set χ = {0,1}, and u' is the output vector uB N Vector after bit flipping operation.
Due to G N And R are triangular matrixes, and the total Euclidean distance in maximum likelihood joint detection decoding can be equal to each symbol vector s i Increment of Euclidean distance e i Is the sum of
Wherein [ G ] above N ] j Represents G N Column j.
And S220, obtaining a plurality of synchronous sets according to the Euclidean distance increment corresponding to each symbol vector.
Based on the above formula (4), if u is used N To u 1 In turn, ofEnumerating bits, each time a symbol i is determined (m consecutive bits are determined), corresponding to a Euclidean distance e i Can be determined. Therefore, in this embodiment, the maximum likelihood joint detection decoding problem can be solved by using depth-first search sphere decoding, where it should be noted that, the depth-first search sphere decoding algorithm only needs to enumerate bits in a space satisfying the polar code encoding rule, and compared with the sphere decoding algorithm detected by the MIMO system, the search space is greatly reduced, so that the complexity of the detection decoding algorithm can be reduced. Wherein, the frozen bit in the input bit does not participate in the enumeration process during the detection decoding process.
In practical application, in order to solve the maximum likelihood joint detection decoding problem by using depth-first search sphere decoding, a plurality of synchronization sets need to be acquired first.
In an embodiment, the step of obtaining a plurality of synchronization sets according to the euclidean distance increment corresponding to each symbol vector in S220 may include: acquiring the determining time of Euclidean distance increment corresponding to each symbol vector; and respectively determining the Euclidean distance increments with the same determination time as a plurality of corresponding synchronous sets.
After the determination time of the euclidean distance increment corresponding to each symbol vector is obtained, the euclidean distance increments with the same determination time can be obtained, and the euclidean distance increments with the same determination time are determined as the same synchronization set. Wherein, if there are multiple different determination times, then multiple corresponding synchronous sets can be obtained
I.e. the number of synchronization sets may be equal to the number of different determined times.
Illustratively, with a polar code
Coding, 16-order quadrature amplitude modulation, 2 × 2 MIMO system as an example, in the MIMO system of polar code coding, the symbol vector s i Is not only dependent on G N Also dependent on R, in this embodimentIn Euclidean distance increment e i Is shown as
In this embodiment, if
Or
Then the corresponding s i Are the information symbols. If the number of information symbols is assumed to be Ls. Wherein the number of information symbols may be equal to 1/2 of the total number of input bits. To obtain
A pre-processing is required, i.e. Ls pairs of bits (u) corresponding to Ls information symbols are enumerated 2i-1 ,u 2i ). As shown in fig. 5
The first row in fig. 5 shows 4 pairs of bits (u) 2i-1 ,u 2i ) In FIG. 5, the output arrow corresponding to the input bit is used to obtain the information symbol, which is based on G N Describes the information bit u i For code word x i (or symbol vector s i ) The influence of the degree of determination determines whether the input bit has a corresponding output arrow, i.e. determines whether the input bit is an information bit or a frozen bit, wherein the information bit has a corresponding output arrow, the frozen bit has no corresponding output arrow, and the two code words form an information symbol s i 。
Specifically, in fig. 5, each slave u i The pointing arrow represents [ G ] N ] i,j Is non-zero, i.e. x j With u i Is changed. In fig. 5 according to the information symbol s i Obtain the Euclidean distance increment e i Is according to R describesModulation symbol pair euclidean distance increment e i Influence of uncertainty, each slave s i Direction e i The arrow of (A) represents [ R ]] j,i Non-zero, the resulting synchronization sets in this example are each
The detection decoding method provided by the embodiment of the application can convert the maximum likelihood detection problem of the MIMO system into the joint ML detection decoding problem, and can solve the joint ML detection decoding problem by adopting a depth-first search sphere decoding algorithm, so that the search space can be greatly reduced, and the complexity of the detection decoding algorithm can be reduced; in addition, the method adopts a joint detection decoding model, channel coding is considered in the MIMO system, detection and decoding are fused, information is fully encoded during detection operation, the error correction performance of the MIMO system can be improved, and the detection complexity is reduced.
The process of decoding and searching each synchronization set in S300 to obtain the target path will be described below. In an embodiment, as shown in fig. 6, the step in S300 may include:
s310, determining a preset search threshold value of decoding search based on a multi-tree search strategy.
Because the initial sphere radius is usually not set in the existing sphere decoding algorithm, the initial sphere radius can be considered as infinite, so that a large amount of unnecessary search processing can be caused, and finally, the convergence rate of the decoding search algorithm is low and the algorithm complexity is high. Therefore, the embodiment of the present application provides a polar code sphere decoding algorithm assisted by a multi-tree search strategy to solve the problem, and the multi-tree search strategy is taken as a depth-first search strategy as an example for explanation.
In practical application, the depth-first search strategy is determinedYi (Chinese character)
Wherein
Is the Euclidean distance D under the condition that the path in the search tree is real u 1 . Due to (1/sigma) 2 )||n|| 2 ～χ 2 (2N t ) So that a constant ε (0) is given<ε < 1) a can be determined such that equation (4) holds.
Before the deep search is started, the preset search threshold of the decoding search may be determined as a σ 2 Wherein a σ can be solved inversely by the formula (4) 2 . If the smallest D among all paths in the search tree 1 Is equal to
The probability of correct decoding is 1-epsilon; if the initial spherical radius cannot be updated during the search, e = α e (0)<α<1) And carrying out a new round of depth search by using a new preset search threshold value, and repeating the steps until a path with the minimum sum of Euclidean distances is found.
And S320, establishing a search tree based on each synchronous set.
Based on all the synchronization sets obtained in the above steps, the synchronization set with the earliest determined time may be screened out first, the input bit corresponding to the euclidean distance increment in the synchronization set with the earliest determined time is determined as the topmost tree node in the search tree, and then the input bit corresponding to the euclidean distance increment in other synchronization sets is determined as the other tree nodes in the search tree according to the sequence of the determined time in sequence. Alternatively, the hierarchy of the search tree may be equal to the total number of synchronization sets, and each hierarchy corresponds to one synchronization set, and it should be noted that the top-most layer to the bottom-most layer of the search tree correspond to the synchronization set with the earliest determined time to the synchronization set with the latest determined time, respectively. With continued reference to the example of FIG. 5, the search tree is a tree structure from level Ls/2 to level 1, where Ls/2 is the total number of synchronization sets and level 1 is the lowest level of the search tree.
As yet another example, if the sets are synchronized
Including e 4 ，
Including e 3 、e 2 、e 1 Then synchronize the sets
Increment of Euclidean distance e in 4 Corresponding input bit is u 7 And u 8 Synchronous collections
Increment of Euclidean distance e in 3 、e 2 、e 1 The corresponding input bits are respectively u 5 And u 6 、u 4 And u 3 、u 2 And u 1 That is, a corresponding search tree is established, the search tree includes two layers of tree nodes, and the topmost tree node is u 7 And u 8 The lowest tree node is u 5 And u 6 、u 4 And u 3 、u 2 And u 1 However, in the present embodiment, each tree node includes only information bits among the input bits, does not include frozen bits, and each tree node in the same layer is the same.
In the depth-first search process, the frozen bits do not need to be enumerated, so that the enumeration sequence of the input bits can be optimized after a synchronous set assisted polar code spherical decoding algorithm is adopted.
Wherein, the top layer in the search tree comprises two tree nodes, based on the two tree nodes, the tree nodes in other levels in the search tree are constructed in sequence, and the branch number of each tree node can be equal to 2 n And n represents the number of information bits in the tree node, and each tree node is the same corresponding to the tree node of the next level.
S330, according to a preset sequence in the search tree, determining an adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree according to the input bits corresponding to each level in the search tree.
Specifically, the preset sequence in the search tree may be an order from the top to the bottom of the search tree, or may be an order from the bottom to the top of the search tree, or of course, may also be a fixed order defined by the search tree. However, in the embodiment of the present application, the preset order is taken as an example of an order from the top to the bottom of the search tree.
In one embodiment, according to a preset sequence in the search tree, sequentially traversing one tree node in each level in the search tree, and calculating an adjacent euclidean distance between two adjacent input bits traversed in any two adjacent levels in the search tree in the traversing process. Optionally, after one or more rounds of traversal are finished, the finally obtained target path includes one tree node in each level in the search tree.
S340, selecting a path meeting the target search condition from the search tree, and determining the path as a target path; the target search condition is that the adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree is smaller than the input bit of a preset search threshold value, and a path comprises a plurality of input bits.
Specifically, the adjacent euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree may be compared with a preset search threshold, the lowest tree node (i.e., input bit) whose adjacent euclidean distance is smaller than the preset search threshold is retained, the lowest tree node whose adjacent euclidean distance is smaller than the preset search threshold is filtered, and all the retained tree nodes are combined to form the target path.
For example, in polarization codes
The search process is described for application in coding, 16-order qam, 2 × 2 MIMO systems, and if there are 4 synchronization sets:
fig. 7 shows the search tree established based on the 4 synchronization sets, and it is shown in the graph of the access of tree nodes and their corresponding path metrics that the correspondence of adjacent euclidean distances between two adjacent tree nodes is also displayed in the graph (labeled numerical values), if the adjacent euclidean distances are greater than or equal to the preset search threshold, the lowest tree node of the adjacent euclidean distances will be filtered out, that is, the lowest tree node will not generate a branch tree node any more, and the adjacent euclidean distances labeled at the filtered tree nodes in the graph are labeled with gray fonts. If the searching is carried out to the tail end of a certain path, namely the lowest layer tree node, the adjacent Euclidean distance is updated to be the lowest layer tree node between the lowest layer tree node and the adjacent upper layer tree node.
In this example, if let epsilon =0.05, the preset search threshold is 42.6, and since any adjacent euclidean distance on the maximum likelihood path (marked by a bold dashed line) is smaller than the preset search threshold, the search process will be ended after the first round of traversal, and the second round of traversal is not required to be executed to implement the tree search operation. Specifically, in the actual processing process, taking fig. 7 as an example, both branches between the preset search thresholds need to be traversed, and may be traversed synchronously or asynchronously, and in the traversing process, a left branch tree node after each tree node is traversed preferentially, after a round of traversal is performed first, a tree node which is not traversed in the previous round of traversal is traversed from a right branch tree node of the tree node at the bottommost layer to the direction of the topmost layer, and a target path finally obtained in this embodiment is the bold dotted path in fig. 7.
Further, the step of determining the target detection decoding result according to the target path and the target detection decoding function in S400 may include: and substituting the sum of all adjacent Euclidean distances corresponding to the target path into a target detection decoding function to obtain a target detection decoding result.
In the embodiment of the present application, the sum of adjacent euclidean distances between all adjacent tree nodes in the target path may be substituted into the target detection decoding function to obtain the target detection decoding result.
The detection decoding method provided by the embodiment of the application can convert the maximum likelihood detection problem of the MIMO system into the joint ML detection decoding problem, and can solve the joint ML detection decoding problem by adopting a depth-first search sphere decoding algorithm, so that the search space can be greatly reduced, and the complexity of the detection decoding algorithm can be reduced.
In order to facilitate understanding of those skilled in the art, the detection and decoding method provided by the present application is described by taking an execution subject as a computer device as an example, and specifically, the method includes:
(1) And determining a symbol vector of each channel based on the input bits received by the communication system and a channel matrix corresponding to each channel of the communication system.
(2) And determining the equivalent receiving vector of each channel according to the symbol vector, the target noise vector and the triangular matrix of each channel.
(3) And determining Euclidean distance increment corresponding to each symbol vector according to the equivalent receiving vector and the symbol vector of each channel.
(4) And acquiring the determining time of the Euclidean distance increment corresponding to each symbol vector.
(5) And respectively determining the Euclidean distance increments with the same determination time as a plurality of corresponding synchronous sets. The synchronization set is a set obtained by combining input bits.
(6) And determining a preset search threshold value of decoding search based on the multi-tree search strategy.
(7) A search tree is built based on the synchronization sets.
(8) And according to a preset sequence in the search tree, determining the adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree according to the input bits corresponding to each level in the search tree.
(9) Selecting a path meeting the target search condition from the search tree and determining the path as a target path; the target search condition is a path of which the adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree is smaller than a preset search threshold value, and the path comprises a plurality of input bits; the target path is the path with the minimum sum of the Euclidean distances in the detection decoding.
(10) And obtaining a target detection decoding function according to the equivalent receiving vector and the symbol vector of each channel.
(11) And substituting the sum of all adjacent Euclidean distances corresponding to the target path into a target detection decoding function to obtain a target detection decoding result.
For the implementation processes in (1) to (11), reference may be specifically made to the description of the above embodiments, and the implementation principles and technical effects thereof are similar and are not described herein again.
It should be understood that although the various steps in the flowcharts of fig. 2-4 and 6 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 and 6 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed sequentially, but may be performed alternately or alternately with other steps or at least some of the other steps.
Based on the same inventive concept, the embodiment of the present application further provides a detection decoding apparatus for implementing the above-mentioned detection decoding method. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the above method, so the specific limitations in one or more embodiments of the detecting and decoding apparatus provided below can refer to the limitations on the detecting and decoding method in the foregoing, and details are not described here again.
In one embodiment, as shown in fig. 8, there is provided a detection decoding apparatus including: a symbol vector determining module 11, a synchronous aggregation module 12, a decoding search module 13 and a detection decoding result determining module 14, wherein:
a symbol vector determining module 11, configured to determine a symbol vector of each channel according to an input bit received by the communication system and a channel matrix corresponding to each channel of the communication system;
a synchronization set module 12, configured to obtain multiple synchronization sets corresponding to input bits according to the symbol vector of each channel; wherein, the synchronous set is a set formed by combining input bits;
a decoding search module 13, configured to perform decoding search on each synchronization set to obtain a target path; the target path is the path with the minimum Euclidean distance in the detection decoding;
and a detection decoding result determining module 14, configured to determine a target detection decoding result according to the target path and the target detection decoding function.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
In one embodiment, the synchronization collection module 12 includes: euclidean distance increment determining unit and synchronous set acquiring unit, wherein:
the Euclidean distance increment determining unit is used for determining Euclidean distance increments corresponding to the symbol vectors according to the equivalent receiving vectors and the symbol vectors of the channels;
and the synchronous set acquisition unit is used for acquiring a plurality of synchronous sets according to the Euclidean distance increment corresponding to each symbol vector.
The detection decoding apparatus provided in this embodiment may implement the method embodiments described above, and the implementation principle and technical effects are similar, which are not described herein again.
In one embodiment, the detection decoding apparatus further includes: an equivalent received vector determination module, wherein:
and the equivalent receiving vector determining module is used for determining the equivalent receiving vector of each channel according to the symbol vector, the target noise vector and the triangular matrix of each channel.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
In one embodiment, the synchronization set acquiring unit is specifically configured to:
acquiring the determining time of Euclidean distance increment corresponding to each symbol vector;
and respectively determining the Euclidean distance increments with the same determination time as a plurality of corresponding synchronous sets.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
In one embodiment, the decoding search module 13 includes: the device comprises a threshold determining unit, a search tree acquiring unit, an Euclidean distance calculating unit and a target path determining unit, wherein:
the threshold value determining unit is used for determining a preset search threshold value of decoding search according to a multi-tree search strategy;
a search tree acquisition unit for establishing a search tree based on each synchronization set;
the Euclidean distance calculating unit is used for determining the adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree according to the preset sequence in the search tree and the input bits corresponding to each level in the search tree;
the target path determining unit is used for selecting a path meeting the target searching condition from the searching tree and determining the path as a target path; the target search condition is a path with adjacent Euclidean distances between any two adjacent input bits in any two adjacent levels in the search tree smaller than a preset search threshold value, and the path comprises a plurality of input bits.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
In one embodiment, the detection and decoding result determining module 14 is specifically configured to:
and substituting the sum of all adjacent Euclidean distances corresponding to the target path into a target detection decoding function to obtain a target detection decoding result.
The detection decoding apparatus provided in this embodiment may implement the method embodiments described above, and the implementation principle and technical effects are similar, which are not described herein again.
In one embodiment, the detection decoding apparatus further includes: a function acquisition module, wherein:
and the function acquisition module is used for acquiring a target detection decoding function according to the equivalent receiving vector and the symbol vector of each channel.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
In one embodiment, the symbol vector determination module 11 includes: a decomposition unit and a modulation processing unit, wherein:
the decomposition unit is used for carrying out orthogonal triangular decomposition on the channel matrix corresponding to each channel to obtain a triangular matrix;
and the modulation processing unit is used for modulating the input bits according to the triangular matrix and the polarization matrix to obtain the symbol vector of each channel.
The detection decoding apparatus provided in this embodiment can perform the above method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
All or part of the modules in the detection and decoding device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 1. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing input bits received by the communication system. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a detection decoding method.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of:
determining a symbol vector of each channel based on input bits received by a communication system and a channel matrix corresponding to each channel of the communication system;
acquiring a plurality of synchronous sets corresponding to input bits according to the symbol vectors of all channels;
decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances corresponding to the detection decoding;
and determining a target detection decoding result according to the target path and the target detection decoding function.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
determining a symbol vector of each channel based on input bits received by a communication system and a channel matrix corresponding to each channel of the communication system;
acquiring a plurality of synchronous sets corresponding to input bits according to the symbol vectors of all channels;
decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances corresponding to the detection decoding;
and determining a target detection decoding result according to the target path and the target detection decoding function.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:
determining a symbol vector of each channel based on input bits received by a communication system and a channel matrix corresponding to each channel of the communication system;
acquiring a plurality of synchronous sets corresponding to input bits according to the symbol vectors of all channels;
decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances corresponding to the detection decoding;
and determining a target detection decoding result according to the target path and the target detection decoding function.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (11)
1. A method for detection decoding, the method comprising:
determining a symbol vector of each channel based on input bits received by a communication system and a channel matrix corresponding to each channel of the communication system;
obtaining a plurality of synchronous sets corresponding to the input bits according to the symbol vectors of the channels; the synchronization set is a set obtained by combining the input bits;
decoding and searching each synchronous set to obtain a target path; the target path is the path with the minimum sum of the Euclidean distances corresponding to the detection decoding;
and determining a target detection decoding result according to the target path and the target detection decoding function.
2. The method of claim 1, wherein obtaining a plurality of synchronization sets corresponding to the input bits according to the symbol vector of each of the channels comprises:
determining Euclidean distance increment corresponding to each symbol vector according to the equivalent receiving vector of each channel and the symbol vector;
and obtaining a plurality of synchronous sets according to Euclidean distance increment corresponding to each symbol vector.
3. The method of claim 2, wherein prior to determining the euclidean distance increment associated with each of the symbol vectors based on the equivalent received vector for each of the channels and the symbol vectors, the method further comprises:
and determining the equivalent receiving vector of each channel according to the symbol vector, the target noise vector and the triangular matrix of each channel.
4. The method of claim 2, wherein obtaining a plurality of the synchronization sets according to the euclidean distance increment corresponding to each of the symbol vectors comprises:
acquiring the determining time of Euclidean distance increment corresponding to each symbol vector;
and respectively determining the Euclidean distance increments with the same determination time as a plurality of corresponding synchronous sets.
5. The method according to any one of claims 1-4, wherein the performing a decoding search on each synchronization set to obtain a target path comprises:
determining a preset search threshold value of decoding search based on a multi-tree search strategy;
establishing a search tree based on each of the synchronization sets;
according to a preset sequence in the search tree, determining an adjacent Euclidean distance between any two adjacent input bits in any two adjacent levels in the search tree according to the input bits corresponding to each level in the search tree;
selecting a path meeting the target search condition from the search tree and determining the path as a target path; the target search condition is a path in which adjacent Euclidean distances between any two adjacent input bits in any two adjacent levels in the search tree are smaller than the preset search threshold, and the path comprises a plurality of input bits.
6. The method according to any one of claims 1-4, wherein said determining a target detection decoding result according to the target path and a target detection decoding function comprises:
and substituting the sum of all adjacent Euclidean distances corresponding to the target path into the target detection decoding function to obtain the target detection decoding result.
7. The method of claim 6, wherein before determining the target detection decoding result according to the target path and the target detection decoding function, the method further comprises:
and obtaining the target detection decoding function according to the equivalent receiving vector and the symbol vector of each channel.
8. The method according to any of claims 1-4, wherein determining the symbol vector for each channel based on the input bits received by the communication system and the channel matrix corresponding to each channel of the communication system comprises:
performing orthogonal triangular decomposition on the channel matrix corresponding to each channel to obtain a triangular matrix;
and modulating the input bits according to the triangular matrix and the polarization matrix to obtain a symbol vector of each channel.
9. An apparatus for detection decoding, the apparatus comprising:
a symbol vector determining module, configured to determine a symbol vector of each channel according to an input bit received by a communication system and a channel matrix corresponding to each channel of the communication system;
a synchronization set module, configured to obtain multiple synchronization sets corresponding to the input bits according to the symbol vector of each channel; the synchronization set is a set obtained by combining the input bits;
the decoding search module is used for performing decoding search on each synchronous set to obtain a target path; the target path is the path with the minimum Euclidean distance in the detection decoding;
and the detection decoding result determining module is used for determining a target detection decoding result according to the target path and the target detection decoding function.
10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 8.
11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 8.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101997652A (en) * | 2009-08-14 | 2011-03-30 | 中兴通讯股份有限公司 | Acceptance detection method and device based on LDPC-MIMO (low density parity check-multiple input multiple output) communication system |
| WO2015131840A1 (en) * | 2014-03-07 | 2015-09-11 | 电信科学技术研究院 | Detection method and apparatus of mimo system |
| EP3059915A1 (en) * | 2015-02-19 | 2016-08-24 | Instutut Mines-Télécom | Tree search-based decoding |
| CN114629534A (en) * | 2022-02-23 | 2022-06-14 | Oppo广东移动通信有限公司 | MIMO detection method and device based on tree search, chip and storage medium |
| CN114731323A (en) * | 2020-11-04 | 2022-07-08 | 华为技术有限公司 | Detection method and device for MIMO system |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008027554A2 (en) * | 2006-08-31 | 2008-03-06 | Interdigital Technology Corporation | Method and apparatus for qr decomposition-based mimo detection and soft bit generation |
| CN103152142A (en) * | 2013-03-20 | 2013-06-12 | 清华大学 | Signal detection method and signal detection device for MIMO (Multiple Input Multiple Output) systems |
| CN109547034B (en) * | 2017-09-22 | 2021-10-01 | 华为技术有限公司 | Decoding method and device, decoder |
| CN115396064B (en) * | 2022-08-16 | 2023-11-24 | 网络通信与安全紫金山实验室 | Detection decoding method, detection decoding device, computer equipment and readable storage medium |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101997652A (en) * | 2009-08-14 | 2011-03-30 | 中兴通讯股份有限公司 | Acceptance detection method and device based on LDPC-MIMO (low density parity check-multiple input multiple output) communication system |
| WO2015131840A1 (en) * | 2014-03-07 | 2015-09-11 | 电信科学技术研究院 | Detection method and apparatus of mimo system |
| EP3059915A1 (en) * | 2015-02-19 | 2016-08-24 | Instutut Mines-Télécom | Tree search-based decoding |
| CN114731323A (en) * | 2020-11-04 | 2022-07-08 | 华为技术有限公司 | Detection method and device for MIMO system |
| CN114629534A (en) * | 2022-02-23 | 2022-06-14 | Oppo广东移动通信有限公司 | MIMO detection method and device based on tree search, chip and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| MOTOROLA: "MIMO and SDMA for EUTRA UL", 《3GPP TSG RAN WG1 LTE ADHOC R1-060889》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024036933A1 (en) * | 2022-08-16 | 2024-02-22 | 网络通信与安全紫金山实验室 | Detection and decoding method and apparatus, computer device and readable storage medium |
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