Quantized Iterative Message Passing Decoders with Low Error Floor for LDPC Codes
Quantized Iterative Message Passing Decoders with Low Error Floor for LDPC Codes
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DOI：
10.1109/tcomm.2013.112313.120917
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发表时间：
2012-12
影响因子：
8.3
通讯作者：
Xiaojie Zhang;P. Siegel
中科院分区：
文献类型：
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作者：
Xiaojie Zhang;P. Siegel
在LDPC码及其基于图的迭代消息传递（MP）解码器中观察到的错误层现象通常归因于易于出错的子结构的存在——在代码的坦纳图表示中，不同地称为近码字、捕获集、吸收集或伪码字。为了降低误差层数，人们提出了许多方法，如设计具有较少子结构的LDPC码或修改译码算法。通过对理想捕获集场景中迭代MP解码的理论分析，我们表明，在文献中观察到的错误层的一个贡献因素可能是解码算法的不精确实现，特别是所使用的消息量化规则。然后，我们提出了一种新的量化方法- (q+1)位准均匀量化-有效地增加了消息的动态范围，从而克服了传统量化方案的局限性。最后，我们使用准均匀量化器对几个LDPC码进行了解码，这些码在传统的定点解码器实现中存在高误差层。性能仿真结果证明，所提出的量化方案可以在最小程度上增加解码器复杂性的情况下，显著降低各种编码的错误层数。
The error floor phenomenon observed with LDPC codes and their graph-based, iterative, message-passing (MP) decoders is commonly attributed to the existence of error-prone substructures - variously referred to as near-codewords, trapping sets, absorbing sets, or pseudocodewords - in a Tanner graph representation of the code. Many approaches have been proposed to lower the error floor by designing new LDPC codes with fewer such substructures or by modifying the decoding algorithm. Using a theoretical analysis of iterative MP decoding in an idealized trapping set scenario, we show that a contributor to the error floors observed in the literature may be the imprecise implementation of decoding algorithms and, in particular, the message quantization rules used. We then propose a new quantization method - (q+1)-bit quasi-uniform quantization - that efficiently increases the dynamic range of messages, thereby overcoming a limitation of conventional quantization schemes. Finally, we use the quasi-uniform quantizer to decode several LDPC codes that suffer from high error floors with traditional fixed-point decoder implementations. The performance simulation results provide evidence that the proposed quantization scheme can, for a wide variety of codes, significantly lower error floors with minimal increase in decoder complexity.