LDPC Codes Achieve List Decoding Capacity

September 13, 2019 ยท Declared Dead ยท ๐Ÿ› IEEE Annual Symposium on Foundations of Computer Science

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Authors Jonathan Mosheiff, Nicolas Resch, Noga Ron-Zewi, Shashwat Silas, Mary Wootters arXiv ID 1909.06430 Category cs.IT: Information Theory Cross-listed cs.CC, math.CO Citations 37 Venue IEEE Annual Symposium on Foundations of Computer Science Last Checked 3 months ago
Abstract
We show that Gallager's ensemble of Low-Density Parity Check (LDPC) codes achieves list-decoding capacity with high probability. These are the first graph-based codes shown to have this property. This result opens up a potential avenue towards truly linear-time list-decodable codes that achieve list-decoding capacity. Our result on list decoding follows from a much more general result: any $\textit{local}$ property satisfied with high probability by a random linear code is also satisfied with high probability by a random LDPC code from Gallager's distribution. Local properties are properties characterized by the exclusion of small sets of codewords, and include list-decodability, list-recoverability and average-radius list-decodability. In order to prove our results on LDPC codes, we establish sharp thresholds for when local properties are satisfied by a random linear code. More precisely, we show that for any local property $\mathcal{P}$, there is some $R^*$ so that random linear codes of rate slightly less than $R^*$ satisfy $\mathcal{P}$ with high probability, while random linear codes of rate slightly more than $R^*$, with high probability, do not. We also give a characterization of the threshold rate $R^*$.
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