LDPC code hard decision decoding method based on matching pursuit

Abstract

The invention provides an LDPC code hard decision decoding method based on matching pursuit, and the method employs a matching pursuit algorithm with Hamming distance as a similarity measure to solvean error pattern according to the characteristic of sparse error pattern. The method is excellent in performance and mainly comprises optimization designs in three aspects: the matching pursuit algorithm uses a Hamming distance to replace an inner product as a similarity measure, so that the matching accuracy in the decoding process is greatly improved; a credibility priority mechanism is introduced in the matching process, so that the possible mismatching condition is reduced; and the credibility is updated in each iteration. Simulation result shows that the error correction performance of the decoding method is obviously superior to that of an existing hard decision algorithm such as a weighted bit flipping (WBF) algorithm, when the error rate is 10<-6>, the error rate of the decoding method is increased by about 1.2 dB compared with that of the WBF algorithm, and when the signal to noise ratio is 8 dB, the error rate of the decoding method is reduced by about 2 orders of magnitude compared with that of the WBF. In addition, the method also maintains the advantages of low complexity of hard decision decoding time, easiness in hardware implementation and the like.

Description

technical field [0001] The invention relates to the field of communication channel coding, in particular to a hard decision decoding method based on matching pursuit LDPC codes. Background technique [0002] LDPC codes have excellent performance and are selected as error correction codes for 5G communication data channels, and are widely used in various communication systems. LDPC codes have two decoding schemes: hard decision and soft decision. Among them, the decoding performance of soft decision can be close to the Shannon limit, but the decoding is complicated, the delay is large, and the requirements for hardware resources are high; the decoding complexity of hard decision is low, and the delay is low. The time is small, but the performance is quite different from the former. It has been a long-term research topic since LDPC codes were proposed to explore good hard-decision decoding methods, improve the error correction capability of LDPC codes, and keep decoding compl...

AI Technical Summary

Problems solved by technology

[0004] However, sparse signal processing is based on the entire real or complex domain, while binary LDPC codes are based on the GF(2) domain. Directly introducing matching pursuit theory into the decoding of LDPC codes will cause many problems, mainly in the following areas: 1. , the traditional matching pursuit algorithm (MP) algorithm uses the inner product of two vectors as the similarity measure to match, and uses the inner product as the coefficient of atomic decomposition, but in binary coding, it is not appropriate to use the inner product to measure the similarity, and the atomic decomposition The coefficient of is not the inner product, but 1 or 0, indicating whether there is an error or no error, which determines that the traditional MP algorithm cannot be directly used for decoding LDPC codes; secondly, in binary coding, similar degree of the same situation (but this problem hardly occurs in the real number field), this brings difficulties to binary matching, that is, the matching tracking algorithm cannot be directly used for the determination of the error position, and the scheme proposed by the present invention will solve these problems. Provide a high-performance hard-decision LDPC code decoding method

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