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Convergence Analysis of Serial Message-Passing Schedules for LDPC Decoding

机译:LDPC解码串行消息传递时间表的收敛分析

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Serial decoding schedules for low-density parity-check (LDPC) codes are described and analyzed. Conventionally, in each iteration all the variable nodes and subsequently all the check nodes send messages to their neighbors ("flooding schedule"). In contrast, in the considered methods, the updating of the nodes is implemented according to a serial schedule. The evolution of the decoding algorithm's computation tree under serial scheduling is analyzed. The analysis shows that it grows twice as fast in comparison to the flooding schedule's computation tree, indicating that the serial schedule propagates information twice as fast in the code's underlying graph. Furthermore, asymptotic analysis of the serial schedule's convergence rate is done using the Density Evolution (DE) algorithm. Applied to various ensembles of LDPC codes, it shows that when working near the ensemble's threshold, for long enough codes the serial schedule is expected to converge in half the number of iterations compared to the standard flooding schedule. This observation is generally proved for the Binary Erasure Channel (BEC) under some likely assumptions. Finally, an accompanying concentration theorem is proved, justifying the asymptotic DE analysis assumptions.
机译:描述和分析了用于低密度奇偶校验(LDPC)代码的串行解码时间表。传统上,在每个迭代中所有可变节点以及随后所有检查节点都向其邻居发送消息(“洪水计划”)。相反,在所考虑的方法中,根据序列计划实现节点的更新。分析了解码算法在串行调度下的计算树的演变。该分析表明,与洪水计划的计算树相比,它比较快速增长,表明串行计划在代码的底层图中快速传播信息两倍。此外,使用密度进化(DE)算法进行串行时间表的收敛速度的渐近分析。应用于LDPC代码的各种集合,它表明,当在合奏的阈值附近工作时,对于足够长的代码,预计与标准洪水计划相比迭代次数的一半序列时间表。在一些可能的假设下,通常证明了这种观察结果。最后,证明了伴随的浓度定理,证明了渐近的DE分析假设。

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