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Density evolution for the simultaneous decoding of LDPC-based slepian-wolf source codes

机译:用于同时解码基于LDPC的le狼狼源代码的密度演化

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This paper deals with the design and analysis of low-density parity-check (LDPC) codes for the Slepian-Wolf problem. The main contribution is a code design method based on a density evolution (DE) analysis for the cases where multiple LDPC codes are simultaneously decoded at the decoder. Good source codes are designed both for memoryless sources and sources with Markov memory. Further, simultaneous decoding is generalized to the case of source splitting, which allows non-corner points of the Slepian-Wolf region to be achieved even for sources with equiprobable marginal distributions
机译:本文涉及对河流狼问题的低密度奇偶校验(LDPC)代码的设计和分析。主要贡献是基于密度进化(DE)分析的代码设计方法,用于在解码器处同时解码多个LDPC代码的情况。良好的源代码都设计用于Markov Memory的记忆源和源。此外,同时解码推广到源分裂的情况下,源极散,甚至甚至可以实现扫掠狼区域的非角点,即使对于具有备用边缘分布的来源也可以实现

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