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关于LDPC码的奇偶检验密度和可验证率

On the Parity-Check Density and Achievable Rates of LDPC Codes

Gil Wiechman, Igal Sason

摘要:

本文介绍了在无记忆二进制输入输出对称信道上传输的二进制线性分组码的奇偶检验矩阵的渐进密度和ML解码下可达到的速率的新界。奇偶检验密度的下限用信道容量和可实现可靠通信的码的速率之间的间隙来表示,并且对于二进制线性分组码的每个序列都是有效的。的界限解决的问题,以前考虑的Sason和Urbanke,如何稀疏的奇偶检验矩阵的二进制线性分组码是作为一个功能的间隙容量。二进制线性分组码的可实现速率的新上界收紧了Burshtein等人先前报道的边界,因此能够在ML解码下获得二进制线性分组码序列的阈值的更严格的上界。将该界应用于低密度奇偶检验(LDPC)码,并用数值方法说明了其紧性的改善。

英文摘要:

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds on the parity-check density are expressed in terms of the gap between the channel capacity and the rate of the codes for which reliable communication is achievable, and are valid for every sequence of binary linear block codes. The bounds address the question, previously considered by Sason and Urbanke, of how sparse can parity-check matrices of binary linear block codes be as a function of the gap to capacity. The new upper bounds on the achievable rates of binary linear block codes tighten previously reported bounds by Burshtein et al., and therefore enable to obtain tighter upper bounds on the thresholds of sequences of binary linear block codes under ML decoding. The bounds are applied to low-density parity-check (LDPC) codes, and the improvement in their tightness is exemplified numerically.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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