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arXiv 0911.4522cs.ITcs.DMmath.IT
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关于图的码可纠错误数

On the Number of Errors Correctable with Codes on Graphs

Alexander Barg, Arya Mazumdar

摘要:

我们研究了从随机图和固定的局部约束码构造的图上的码(广义低密度奇偶校验码,或LDPC码)的集合,以及它们对超图上的码的扩展。已知这些集合中的码的平均最小距离随码长线性增长。我们表明,这些代码可以纠正一个线性增长的简单的迭代解码算法下的错误数量。特别是,我们证明了这个属性扩展到由汉明码和其他代码的最小距离小的并行级联构造的代码。以前已知的结果,证明这个属性的图形代码依赖于图形扩展,并需要选择本地代码与大的距离相对于它们的长度。

英文摘要:

We study ensembles of codes on graphs (generalized low-density parity-check, or LDPC codes) constructed from random graphs and fixed local constrained codes, and their extension to codes on hypergraphs. It is known that the average minimum distance of codes in these ensembles grows linearly with the code length. We show that these codes can correct a linearly growing number of errors under simple iterative decoding algorithms. In particular, we show that this property extends to codes constructed by parallel concatenation of Hamming codes and other codes with small minimum distance. Previously known results that proved this property for graph codes relied on graph expansion and required the choice of local codes with large distance relative to their length.

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