Decoding method of ldpc code based on dynamic selection strategy with variable message update range

Abstract

The invention particularly relates to an LDPC code decoding method based on a dynamic selection strategy with a variable message updating range. According to the decoding method, the current decodingstate is judged by counting the number of the check nodes which do not meet a check equation during the decoding updating process, so that the current decoding state is dynamically adjusted into an appropriate updating range. When the decoding state is good, the decoding updating method selects a larger updating range for decoding, so that more updated information is transmitted, and the decodingconvergence speed is increased. When the decoding state is deteriorated, the decoding updating method reduces the number of rings formed in the range by reducing the updating range, so that the propagation of greedy trend on the rings is inhibited, and the decoding error correction performance is improved. According to the present invention, the updating range can be reasonably adjusted accordingto the decoding state, the greedy of the dynamic decoding updating method is effectively inhibited, and the decoding performance, the convergence performance and the throughput performance are greatlyimproved.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to an LDPC code decoding method based on a dynamic selection strategy with a variable message update range. Background technique [0002] In 1962, Gallager proposed the LDPC (Low Density Parity Check Codes) code for the first time. However, due to the hardware conditions at that time, this linear block code with excellent performance did not attract enough attention. In 1981, thanks to the proposal and application of the Tanner graph, the research on LDPC codes has made great progress. In 1995, MacKey et al. made sufficient theoretical and experimental proofs on the performance, construction method, encoding method, and decoding method of LDPC codes. Since then, this LDPC code that can approach the Shannon limit has aroused strong research interest in the academic circle. The sparsity of the LDPC code means that there are very few non-zero elements in the check matrix H of t...

AI Technical Summary

Problems solved by technology

If this update transfer trend propagates along the edges on the ring, it will eventually cause a small number of edges to be updated repeatedly, thus occupying too many decoding resources and forming a greedy problem in the dynamic scheduling strategy.

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