Decoding Method of High Density Linear Block Code Based on Neural Network

Abstract

The invention discloses a high-density linear block code decoding method based on a neural network. The specific steps are: (1) constructing a noise reduction neural network; (2) constructing an error correction neural network; (3) constructing codeword rearrangement and multiplication (4) generate a training set; (5) train a noise reduction neural network and an error correction neural network; (6) obtain a neural network decoder; (7) the decoder outputs the final decoding result. The invention constructs a decoding neural network. Before the received high-density linear block code words are subjected to error correction processing, noise reduction processing is performed first, thereby further improving the decoding accuracy rate. The code word rearrangement multiplier is adopted. , so that the cyclic neural network can learn the relationship between the symbol sequences in the multi-ary codeword, so that the decoding neural network can decode the multi-ary RS code well, and the applicability of the present invention is improved.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a neural network-based high-density linear block code decoding method in the technical field of wireless communication. The invention can be used for decoding high-density linear block codes in cellular communication, satellite communication and military systems. Background technique [0002] High-density linear block codes add certain code bits for error control in a certain way to correct some random error bits. When the code length is short and medium, its error correction performance is close to the theoretical value. The receiving end decodes according to the corresponding rules, but errors are prone to occur during the decoding process. In order to improve the overall performance of the information transmission system, a decoding method suitable for high-density linear block codes is needed. At present, the first decoding method of high-density linear block co...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that due to the binary bit mapping of the codeword, a large amount of channel soft information is ignored, which leads to the degradation of the decoding performance of the high-density linear block code.

The disadvantage of this method is that when the variable node message is updated and decoded, there are a large number of short loops in the Tanner graph of the multi-ary RS code, so that the same message is repeatedly transmitted in the Tanner graph, making the BP decoding method inapplicable The result of decoding the RS code

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