CN-119865286-B - SCMA (stream control message) based detection and decoding method and related equipment thereof

CN119865286BCN 119865286 BCN119865286 BCN 119865286BCN-119865286-B

Abstract

The application discloses a detection and decoding method based on SCMA and related equipment thereof, relating to the technical field of communication, wherein the detection and decoding method based on SCMA comprises the steps of receiving symbol sequence data corresponding to a plurality of users; and carrying out iterative decoding and detection on the symbol sequence data through a preset expected propagation algorithm and a soft output decoder, and outputting bit sequence information after a preset stopping condition is reached, wherein the symbol sequence data comprises a plurality of variable nodes and a plurality of functional nodes, and the variable nodes and the functional nodes are iteratively updated based on priori information. The application reduces the error rate in the data transmission process.

Inventors

ZHANG KE
LI CHUNJIE
LIN WENCHAO
JIAO JIAN
MA SU
WANG YE
ZHANG QINYU

Assignees

鹏城实验室
哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院)

Dates

Publication Date: 20260505
Application Date: 20250116

Claims (10)

1. A SCMA-based detection and decoding method, applied to a receiving end, the method comprising: receiving symbol sequence data corresponding to a plurality of users; And carrying out iterative decoding and detection on the symbol sequence data through a preset expected propagation algorithm and a soft output decoder, and outputting bit sequence information after a preset stop condition is reached, wherein the symbol sequence data comprises a plurality of variable nodes and a plurality of functional nodes, the iterative decoding and detection on the symbol sequence data are carried out based on an extended factor graph, the extended factor graph is constructed by describing an asynchronous interference relation among the symbol sequence data and comprises a plurality of factor graphs corresponding to the transmission times, the variable nodes and the functional nodes are iteratively updated based on priori information, and the variable nodes and the functional nodes are initialized based on the priori information before iteration starts.
2. The method of claim 1, wherein the step of iteratively decoding and detecting the symbol sequence data by a predetermined desired propagation algorithm and a soft output decoder, and outputting bit sequence information after a predetermined stop condition is reached, comprises: carrying out iterative updating processing on the symbol sequence data through a preset expected propagation algorithm to obtain an external information log-likelihood ratio; Inputting the external information log-likelihood ratio to a soft output decoder, and decoding the external information log-likelihood ratio based on the soft output decoder to obtain soft information; and carrying out iterative exchange processing on the soft information between a detector corresponding to a preset expected propagation algorithm and a soft output decoder until a preset stopping condition is reached, and outputting bit sequence information.
3. The method of claim 2, wherein before the step of iteratively updating the symbol sequence data by a preset expected propagation algorithm to obtain the extrinsic information log likelihood ratio, the method further comprises: Constructing an extended factor graph based on the asynchronous interference relation between the symbol sequence data; The extended factor graph comprises a plurality of factor graphs corresponding to transmission times, each factor graph comprises a plurality of prior nodes, variable nodes and functional nodes, the prior nodes of the extended factor graph represent prior probabilities of codewords, the variable nodes represent transmission codewords, and the functional nodes represent received discrete symbols.
4. The method of claim 3, wherein the step of performing iterative update processing on the symbol sequence data by a preset expected propagation algorithm to obtain the extrinsic information log likelihood ratio comprises: Based on the prior node, the variable node and the functional node, determining posterior probability corresponding to the symbol sequence data, first transfer information transferred from the variable node to the functional node and second transfer information transferred from the functional node to the variable node; Converting the first transfer information and/or the second transfer information into Gaussian distribution information based on the first transfer information and/or the second transfer information to obtain first distribution information and second distribution information; Respectively carrying out iterative computation on the first distribution information and the second distribution information to obtain updated first transfer information and updated second transfer information; and determining the external information log-likelihood ratio based on the updated first transfer information and the updated second transfer information.
5. The method of claim 2, wherein said decoding the log likelihood ratio of the extrinsic information based on the soft output decoder to obtain soft information comprises: splitting the extrinsic information log-likelihood ratio into a first estimated bit sequence and a second estimated bit sequence based on the soft output decoder; And decoding the first estimated bit sequence and the second estimated bit sequence according to a preset number of decoding paths to obtain soft information.
6. The method of claim 5, wherein the step of outputting the bit sequence information after the preset stop condition is reached, comprises: And stopping decoding when the generated first estimated bit sequence and the generated second estimated bit sequence reach a preset stopping condition, and outputting a bit sequence, wherein the preset stopping condition comprises that elements corresponding to least reliable bases in the first estimated bit sequence and the second estimated bit sequence are updated when a stopping criterion of a soft output decoder is met, and elements corresponding to most reliable bases in the first estimated bit sequence and the second estimated bit sequence are not updated.
7. The method of claim 2, wherein said decoding the log likelihood ratio of the extrinsic information based on the soft output decoder to obtain soft information further comprises: if the coding length of the symbol sequence data is smaller than a preset length threshold value, decoding the external information log likelihood ratio based on a soft output decoder algorithm of an ordered likelihood decoder to obtain soft information; And if the coding length of the symbol sequence data is greater than or equal to a preset length threshold value, decoding the external information log likelihood ratio based on a belief propagation algorithm to obtain soft information.
8. An SCMA-based detection and decoding apparatus, the apparatus comprising: The receiving module is used for receiving symbol sequence data corresponding to a plurality of users; The decoding module is used for carrying out iterative decoding and detection on the symbol sequence data through a preset expected propagation algorithm and a soft output decoder, and outputting bit sequence information after reaching a preset stop condition, wherein the symbol sequence data comprises a plurality of variable nodes and a plurality of functional nodes, the iterative decoding and detection on the symbol sequence data are carried out based on an extended factor graph, the extended factor graph is constructed by describing an asynchronous interference relation among the symbol sequence data and comprises a plurality of sub-factor graphs corresponding to transmission times, the variable nodes and the functional nodes are iteratively updated based on priori information, and the variable nodes and the functional nodes are initialized based on the priori information before iteration starts.
9. A storage medium, characterized in that the storage medium is a computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of SCMA-based detection and decoding according to any of claims 1 to 7.
10. A computer program product, characterized in that it comprises a computer program which, when executed by a processor, implements the steps of SCMA-based detection and decoding according to any of claims 1 to 7.

Description

SCMA (stream control message) based detection and decoding method and related equipment thereof Technical Field The application relates to the technical field of communication, in particular to a detection and decoding method based on SCMA and related equipment thereof. Background In satellite-to-ground communication, sparse Code Multiple Access (SCMA) is one of multiple access candidate technologies expected to be applied in satellite communication, and in related technologies, a joint detection and decoding (joint detection and decoding, JDD) scheme is proposed, where SCMA detection and low-density parity check (LDPC) code decoding are combined under a joint sparse map, and in this way, the method is based on the assumption that multi-user signals are completely synchronized at a receiving end. However, in satellite-to-ground communication, if strict synchronization is to be achieved, frequent interaction between a large-scale satellite and a large number of terminals cannot be avoided, which leads to huge signaling overhead and additional power consumption, and high delay and high actual error rate can occur. The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present application and is not intended to represent an admission that the foregoing is prior art. Disclosure of Invention The application mainly aims to provide a detection and decoding method based on SCMA and related equipment thereof, and aims to solve the technical problems of high delay and higher actual error rate in satellite-to-ground communication in the related technology. To achieve the above object, the present application proposes an SCMA-based detection and decoding, including: receiving symbol sequence data corresponding to a plurality of users; And carrying out iterative decoding and detection on the symbol sequence data through a preset expected propagation algorithm and a soft output decoder, and outputting bit sequence information after a preset stopping condition is reached, wherein the symbol sequence data comprises a plurality of variable nodes and a plurality of functional nodes, and the variable nodes and the functional nodes are iteratively updated based on priori information. In an embodiment, the step of iteratively decoding and detecting the symbol sequence data by presetting an expected propagation algorithm and a soft output decoder, and outputting bit sequence information after reaching a preset stop condition includes: carrying out iterative updating processing on the symbol sequence data through a preset expected propagation algorithm to obtain an external information log-likelihood ratio; Inputting the external information log-likelihood ratio to a soft output decoder, and decoding the external information log-likelihood ratio based on the soft output decoder to obtain soft information; and carrying out iterative exchange processing on the soft information between a detector corresponding to a preset expected propagation algorithm and a soft output decoder until a preset stopping condition is reached, and outputting bit sequence information. In an embodiment, before the step of performing iterative update processing on the symbol sequence data by presetting an expected propagation algorithm to obtain the external information log likelihood ratio, the method further includes: Constructing an extended factor graph based on the asynchronous interference relation between the symbol sequence data; The extended factor graph comprises a plurality of factor graphs corresponding to transmission times, each factor graph comprises a plurality of prior nodes, variable nodes and functional nodes, the prior nodes of the extended factor graph represent prior probabilities of codewords, the variable nodes represent transmission codewords, and the functional nodes represent received discrete symbols. In an embodiment, the step of performing iterative update processing on the symbol sequence data by presetting an expected propagation algorithm to obtain an extrinsic information log likelihood ratio includes: Based on the prior node, the variable node and the functional node, determining posterior probability corresponding to the symbol sequence data, first transfer information transferred from the variable node to the functional node and second transfer information transferred from the functional node to the variable node; Converting the first transfer information and/or the second transfer information into Gaussian distribution information based on the first transfer information and/or the second transfer information to obtain first distribution information and second distribution information; Respectively carrying out iterative computation on the first distribution information and the second distribution information to obtain updated first transfer information and updated second transfer information; and determining the external information log-likelihood ratio based on