Singleton-type bounds for list-decoding and list-recovery, and related results1

IF 0.9 2区 数学 Q2 MATHEMATICS
Eitan Goldberg , Chong Shangguan , Itzhak Tamo
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引用次数: 1

Abstract

List-decoding and list-recovery are important generalizations of unique decoding and receive considerable attention over the years. We study the optimal trade-off among the list-decoding (resp. list-recovery) radius, the list size, and the code rate, when the list size is constant and the alphabet size is large (both compared with the code length). We prove a new Singleton-type bound for list-decoding, which, for a wide range of parameters, is asymptotically tight up to a 1+o(1) factor. We also prove a Singleton-type bound for list-recovery, which is the first such bound in the literature. We apply these results to obtain near optimal lower bounds on the list size for list-decodable and list-recoverable codes with rates approaching capacity.

Moreover, we show that under some indivisibility condition of the parameters and over a sufficiently large alphabet, the largest list-decodable nonlinear codes can have much more codewords than the largest list-decodable linear codes. Such a large gap is not known to exist in unique decoding. We prove this by a novel connection between list-decoding and the notion of sparse hypergraphs in extremal combinatorics.

Lastly, we show that list-decodability or recoverability implies in some sense good unique decodability.

列表解码和列表恢复的单例类型边界,以及相关结果
列表解码和列表恢复是唯一解码的重要概括,多年来受到了相当多的关注。我们研究了列表解码算法之间的最优权衡。列表(恢复)半径、列表大小和码率,当列表大小不变且字母表大小较大时(两者都与代码长度相比)。我们证明了列表解码的一个新的单例类型界,对于大范围的参数,它是渐近紧密的,直到1+ 0(1)个因子。我们还证明了列表恢复的一个单例类型界,这是文献中第一个这样的界。我们应用这些结果来获得列表可解码和列表可恢复代码的列表大小的近似最优下界,其速率接近容量。此外,我们还证明了在参数不可分的条件下,在足够大的字母表上,最大的列表可解码的非线性码可以比最大的列表可解码的线性码具有更多的码字。如此大的差距在唯一解码中是不存在的。我们通过极值组合中列表解码与稀疏超图概念之间的新联系证明了这一点。最后,我们证明了列表可解码性或可恢复性在某种意义上意味着良好的唯一可解码性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.90
自引率
9.10%
发文量
94
审稿时长
12 months
期刊介绍: The Journal of Combinatorial Theory publishes original mathematical research concerned with theoretical and physical aspects of the study of finite and discrete structures in all branches of science. Series A is concerned primarily with structures, designs, and applications of combinatorics and is a valuable tool for mathematicians and computer scientists.
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