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On Trapping Sets and Guaranteed Error Correction Capability of LDPC Codes and GLDPC Codes

机译:LDPC码和GLDPC码的陷阱集和保证的纠错能力

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The relation between the girth and the guaranteed error correction capability of ¿ -left-regular low-density parity-check (LDPC) codes when decoded using the bit flipping (serial and parallel) algorithms is investigated. A lower bound on the size of variable node sets which expand by a factor of at least 3 ¿/4 is found based on the Moore bound. This bound, combined with the well known expander based arguments, leads to a lower bound on the guaranteed error correction capability. The decoding failures of the bit flipping algorithms are characterized using the notions of trapping sets and fixed sets. The relation between fixed sets and a class of graphs known as cage graphs is studied. Upper bounds on the guaranteed error correction capability are then established based on the order of cage graphs. The results are extended to left-regular and right-uniform generalized LDPC codes. It is shown that this class of generalized LDPC codes can correct a linear number of worst case errors (in the code length) under the parallel bit flipping algorithm when the underlying Tanner graph is a good expander. A lower bound on the size of variable node sets which have the required expansion is established.
机译:研究了使用位翻转(串行和并行)算法解码时的周长与γ-左规则低密度奇偶校验(LDPC)码的纠错能力之间的关系。根据摩尔定律,发现可变节点集的大小的下界至少扩展了3×4倍。该界限与众所周知的基于扩展器的参数相结合,导致保证的纠错能力的下界。使用捕获集和固定集的概念来表征位翻转算法的解码失败。研究了固定集与称为笼图的一类图之间的关系。然后,根据笼形图的顺序确定保证的纠错能力的上限。结果扩展到左规则和右均匀的通用LDPC码。结果表明,当基础Tanner图是一个良好的扩展器时,在并行位翻转算法下,此类通用LDPC码可以纠正线性数量的最坏情况错误(在代码长度中)。建立了具有所需扩展的变量节点集的大小的下限。

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