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中国邮电高校学报：英文版

Novel modified min-sum decoding algorithm for low-density parity-check codes

Haiyang Liu, Wenze Qu, Bin Liu, Jiangpeng Li, Shi-dong LUO, Jie Chen

Published Aug 1, 2010• 8 citations
Publisher
DOI
10.1016/s1005-8885(09)60479-9

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The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance over a wide range of signal-to-noise ratios. Moreover, we propose modifications to the min-sum algorithm that improve the performance by a few tenths of a decibel with just a small increase in decoding complexity. A quantized version of these modified algorithms is also studied. It is shown that, when optimized, modified quantized min-sum algorithms perform very close to, and in some cases even slightly outperform, the ideal belief-propagation algorithm at observed error rates.
Error floor properties of low-density parity-check(LDPC)codes using different decoding algorithms were statistically analyzed utilizing test data from a hardware evaluation platform.The analysis shows that the number of residual error bits in an error codeword after decoding failure using the sum-product(SP)algorithm or the modified min-sum(MMS)algorithm is usually quite small;therefore,LDPC codes can serve as the inner code in a concatenated coding system to achieve an ultra low bit error rate.The analysis also shows that SP algorithm is more suitable for a concatenated coding system than MMS algorithm since less residual error bits occur when using the SP algorithm.Concatenated codes based on the analysis achieve bit error rates lower than 10-10 with a low decoding threshold.