Method for judging decode halt of LDPC code based on checksum error mode

Abstract

The invention provides a LDPC code decoding stopping decision method based on checksum error mode; checksum variation characteristics are adopted to perform decoding stopping decision; when the iteration decoding times exceeds the set minimum iteration times K, and the checksum is stable and constant in continuous S iteration times, the stopping iteration decoding is judged. The invention directly controls the iteration times through the checksum variation characteristics, and introduces the minimum iteration times for starting the decoding stopping design criterion. The simulation results indicate that the invention greatly reduces the average iteration times in medium-low noise-signal ratio area; meanwhile, the influence on the decoding performance of high noise-signal ratio area from decoding stopping criterion is eliminated at the same time; besides, the LDPC code decoding stopping decision method based on checksum error mode has very low computational complexity.

Description

technical field [0001] The invention belongs to the decoding control field of low-density parity check codes, in particular to a decoding stop judgment method of LDPC codes based on a checksum error mode. technical background [0002] Low-density parity-check (LDPC, Low-Density Parity-Check) codes have performance close to the Shannon limit when using the belief-propagation (BP, belief-propagation) algorithm for iterative decoding, and its decoding complexity and average iteration amount, The calculation amount of the check node is related to the number of active nodes in each iteration. [0003] The LDPC code is a linear block code represented by a sparse parity check matrix H. Except a small part of the parity check matrix elements are not zero, most of the others are 0. LDPC codes can also be described by a sparse bipartite graph. Suppose the sparse check matrix H is an M×N matrix, then the corresponding bipartite graph G is composed of N variable nodes, M check nodes a...

AI Technical Summary

Problems solved by technology

[0007] The problem caused by this stopping criterion is: in the low and medium signal-to-noise ratio (SNR, signal-to-noise ratio) area, a large number of error frames cannot be successfully decoded even by increasing the number of iterations, but the BP iterative decoding algorithm still The decoding can only be stopped when the maximum number of iterations is reached, resulting in a significant increase in the average number of iterations, increased decoding complexity, and increased power consumption.

[0012] The selection of the threshold parameters in the above points 2 and 3 affects each other, and the selection is difficult. When the threshold parameter is not selected properly, the decoding performance in the high SNR area will be reduced.

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