Low-complexity LDPC dynamic scheduling decoding updating method based on variable node reliability

Abstract

Disclosed in the invention is a low-complexity LDPC dynamic scheduling decoding updating method based on variable node reliability. On the basis of point residual of variable nodes, by using an oscillation selection theorem and the dynamic selection strategy of a variable node check criteria, variable nodes which carry reliable extrinsic information are selected to be updated. The method not only takes the residual as a measurement, but also sets the oscillation selection theorem and the check criteria of variable nodes to classify all of the variable nodes into several categories in turn according to the reliability level and magnitude of the extrinsic information. In a set of variable nodes carrying reliable extrinsic information, the variable node with the largest residual is selected to be updated in priority. The method can take full advantage of the characteristic of dynamic change of information during the decoding process, so that the information of the variable nodes can be transmitted to other nodes rapidly, which improves decoding performance.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a low-complexity LDPC dynamic scheduling decoding update method based on variable node reliability. Background technique [0002] In 1962, Gallager proposed the LDPC code for the first time in his doctoral dissertation, and made a comprehensive description of the code's definition, representation method, encoding method and decoding method. However, due to the limitations of technical conditions at that time, LDPC codes did not receive enough attention from researchers. It was not until 1996 that MacKey and Neal conducted in-depth research on the performance of LDPC codes based on the Tanner diagram. At the same time, they found that the error correction performance of LDPC codes approached the Shannon limit when the code length was long enough, which set off an upsurge of research on LDPC codes in the field of coding. . Judging from the research results in the past two ...

AI Technical Summary

Problems solved by technology

[0005] Although the decoding algorithms mentioned above have proposed different solutions to the problem of LDPC dynamic scheduling strategy, there are still some common problems in dynamic scheduling decoding: one is greedy

Second, the selection method of variable nodes and edges in the decoding process needs to be adjusted

Third, the complexity of the dynamic scheduling decoding strategy is too high

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