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arXiv 2408.12946cs.ITmath.IT
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基于隐藏码字的递归Plotkin构造的软判决译码

Soft Decision Decoding of Recursive Plotkin Constructions Based on Hidden Code Words

Martin Bossert

AI总结:

利用递归Plotkin构造码字的隐藏码字特性,提出了仅使用加法、比较和符号操作的低复杂度软判决译码器,并基于RM码构造了两类新颖的半速率码。

摘要:

Plotkin构造将两个码组合成一个长度加倍的码。它可以递归地应用。Reed-Muller (RM) 码类是一个特例。此外,一类特殊的广义级联码 (GCC) 也可以描述为递归Plotkin构造。利用递归Plotkin构造所构造码字的特性,我们提出了新颖的软判决译码器。这些译码器基于对隐藏码字的译码,这些隐藏码字内在地包含在构造的码字中,可以通过加上整个码字的特定部分来揭示。主要思想是使用不止一种译码变体,其中每种变体从对不同的隐藏码字进行译码开始。最终的译码决策从所使用变体的决策中选择最佳者。使用的变体越多,性能就越接近最大似然 (ML) 译码性能。对于ML性能未知的情况,这通过一个ML界得到了验证。该译码算法仅使用加法、比较和符号操作。此外,由于递归结构,仅需对相对较短的码进行译码,因此译码复杂度非常低。另外,我们介绍了基于使用RM码的递归Plotkin构造的两类新颖的半速率码。

英文摘要:

The Plotkin construction combines two codes to a code of doubled length. It can be applied recursively. The class of Reed-Muller (RM) codes is a particular example. Also, a special class of generalized concatenated codes (GCC) can be described as recursive Plotkin construction. Exploiting a property of the code words constructed by the recursive Plotkin construction, we present novel soft-decision decoders. These are based on the decoding of hidden code words which are inherent contained in the constructed code words and can be uncovered by adding particular parts of the overall code word. The main idea is to use more than one decoding variant where each variant starts with the decoding of a different hidden code word. The final decoding decision selects the best of the decisions of the used variants. The more variants are used the closer the performance gets to the maximum-likelihood (ML) decoding performance. This is verified by an ML-bound for the cases where the ML performance is not known. The decoding algorithms use only additions, comparisons, and sign operations. Further, due to the recursive structure, only relatively short codes have to be decoded, thus, the decoding complexity is very low. In addition, we introduce two novel classes of half-rate codes based on recursive Plotkin constructions with RM codes.

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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