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 field of decoding control of low-density parity-check codes, and particularly relates to a decoding stop decision method of an LDPC code based on a checksum error mode. technical background [0002] Low-Density Parity-Check (LDPC, Low-Density Parity-Check) codes have the performance of approaching Shannon limit when adopting the belief-propagation (BP, belief-propagation) algorithm for iterative decoding. 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 check matrix H. Except for a small part of the check matrix elements that are not zero, most of the other check matrix elements are zero. Sparse bipartite graphs can also be used to describe LDPC codes. Suppose the sparse check matrix H is an M×N matrix, then the corresponding bipartite graph G is composed ...

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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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