论文标题
重新访问有序统计数据解码：距离分布和解码规则
A Revisit to Ordered Statistics Decoding: Distance Distribution and Decoding Rules
论文作者
论文摘要
本文重新讨论了有序的统计解码（OSD）。它通过表征OSD算法的后处理阶段中从密码字估计到接收顺序的统计属性，演变和加权锤距离的统计特性，演变和分布，对OSD算法进行了全面的分析。我们证明，锤距和加权锤距分布可以被描述为捕获解码误差概率和代码权重枚举器的混合模型。仿真和数值结果表明，我们提出的统计方法可以准确描述距离分布。基于这些分布并旨在降低解码的复杂性，提出了几种技术，包括停止规则和丢弃规则，并因此分析了它们的解码错误性能和复杂性。解码各种EBCH代码的仿真结果表明，所提出的技术可以显着降低解码的复杂性，而解码误差性能的损失可忽略不计。
This paper revisits the ordered statistics decoding (OSD). It provides a comprehensive analysis of the OSD algorithm by characterizing the statistical properties, evolution and the distribution of the Hamming distance and weighted Hamming distance from codeword estimates to the received sequence in the reprocessing stages of the OSD algorithm. We prove that the Hamming distance and weighted Hamming distance distributions can be characterized as mixture models capturing the decoding error probability and code weight enumerator. Simulation and numerical results show that our proposed statistical approaches can accurately describe the distance distributions. Based on these distributions and with the aim to reduce the decoding complexity, several techniques, including stopping rules and discarding rules, are proposed, and their decoding error performance and complexity are accordingly analyzed. Simulation results for decoding various eBCH codes demonstrate that the proposed techniques can significantly reduce the decoding complexity with a negligible loss in the decoding error performance.
