Mixed iterative decoding method for LDPC-RS two-dimensional product code

Abstract

The invention relates to a mixed iterative decoding method for an LDPC-RS two-dimensional product code in the technical field of communication system channel decoding. According to a received LDPC-RS product code block, log-SPA soft-decision decoding is conducted on LDPC codons of each row, bit soft value information after the decoding and soft value information corresponding to the edge of a bipartite graph are stored; improved WBF decoding is conducted on LDPC rows failed in the log-SPA soft-decision decoding and estimated bit error patterns of the rows failed in decoding can be returned through an improved WBF algorithm; when the estimated error patterns can be corrected by following RS, LDPC hard-decision decoding, RS+LDPC hard-decision decoding is converted; if all errors can not be corrected after one time of iteration is finished, bit soft values corresponding to the rows which is confirmed to be right after the hard-decision decoding are corrected and iteration of the next round is conducted. According to the mixed iterative decoding method for the LDPC-RS two-dimensional product code, the problem that when LDPC-RS is decoded through an SISO decoding structure, an RS soft-decision decoder is high in complexity. Meanwhile, compared with simple LDPC+RS cascading decoding, the mixed iterative decoding method for the LDPC-RS two-dimensional product code improves codon correction performance.

Description

Technical field: [0001] The invention relates to the technical field of channel decoding in the field of communication technology, in particular to a mixed and iterative decoding method of LDPC-RS two-dimensional product codes. technical background: [0002] During the transmission of digital signals, various errors such as random errors and burst errors are often generated in the transmitted data stream due to reasons such as noise and interference. The concept of the product code was first proposed by P.Elias in 1954. It consists of two linear block codes of row code and column code as component code words. The two-dimensional product code arranges the information symbols into a two-dimensional information matrix, and encodes each row and column according to the coding rules of row code and column code respectively. It can be seen that this codeword is an effective way to construct long codes from short component codewords. It combines interleaving technology and error co...

AI Technical Summary

Problems solved by technology

The LDPC codeword consists of a variety of decoding methods, each with its own advantages and disadvantages: the logarithmic sum-product algorithm (log-SPA) and its simplified algorithm based on the sum-product algorithm (Sum-Product Algorithm, SPA) and its simplified algorithm are all soft-decision decoding algorithms. Its decoding performance is better than other decoding algorithms, but its complexity is relatively high; the performance and complexity of the Weighted Bit Flipping (WBF) algorithm are between the soft-decision and hard-decision decoding methods. Decoding estimates the position of the erroneous bits by calculating the inversion function value corresponding to each bit and flips them; hard decision decoding is suitable for decoding LDPC codewords on binary erasure channels, if the position of the bit is not known do not form a stopping set (stopping set) with each other, and can be successfully decoded using a hard-decision decoding scheme

However, the complexity of the soft-decision decoder of the RS codeword is relatively high, and the use of the SISO turbo decoding framework for LDPC-RS product code decoding means that the computational complexity is greatly increased to achieve performance improvement

Therefore, the SISO turbo decoding framework is not suitable for LDPC-RS two-dimensional product codewords

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