A Threshold-Based Min-Sum Algorithm to Lower the Error Floors of Quantized LDPC Decoders
A Threshold-Based Min-Sum Algorithm to Lower the Error Floors of Quantized LDPC Decoders
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DOI：
10.1109/tcomm.2020.2969902
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发表时间：
2020-04-01
影响因子：
8.3
通讯作者：
Fuja, Thomas E.
中科院分区：
文献类型：
--
作者：
Hatami, Homayoon;Mitchell, David G. M.;Fuja, Thomas E.
对于低密度奇偶校验（LDPC）码的译码，衰减最小和算法（AMSA）和偏移最小和算法（OMSA）在低信噪比（SNR）下的性能优于传统最小和算法（MSA），即，在误码率曲线的“瀑布区域”中。本文表明，量化解码器，MSA实际上优于AMSA和OMSA的“错误平层”区域，所有三种算法遭受相对较高的错误平层。这促使引入经修改的MSA，其被设计为在所有SNR上优于MSA、AMSA和OMSA。新算法基于陷阱集是量化LDPC译码器错误平层的主要原因这一假设。通过一个基于陷阱集的性能估计工具验证了新算法的有效性，并指导了算法参数的选择。我们还表明，新算法的实现复杂度仅略高于AMSA或OMSA。最后，新算法的仿真性能，使用几类LDPC码（包括空间耦合LDPC码），优于MSA，AMSA，和OMSA在所有SNR。
For decoding low-density parity-check (LDPC) codes, the attenuated min-sum algorithm (AMSA) and the offset min-sum algorithm (OMSA) can outperform the conventional min-sum algorithm (MSA) at low signal-to-noise-ratios (SNRs), i.e., in the "waterfall region" of the bit error rate curve. This paper demonstrates that, for quantized decoders, MSA actually outperforms AMSA and OMSA in the "error floor" region, and that all three algorithms suffer from a relatively high error floor. This motivates the introduction of a modified MSA that is designed to outperform MSA, AMSA, and OMSA across all SNRs. The new algorithm is based on the assumption that trapping sets are the major cause of the error floor for quantized LDPC decoders. A performance estimation tool based on trapping sets is used to verify the effectiveness of the new algorithm and also to guide parameter selection. We also show that the implementation complexity of the new algorithm is only slightly higher than that of AMSA or OMSA. Finally, the simulated performance of the new algorithm, using several classes of LDPC codes (including spatially coupled LDPC codes), is shown to outperform MSA, AMSA, and OMSA across all SNRs.