Computer Science / Computational Complexity
Computer Science / Information Theory
Mathematics / math.CO
Mathematics / math.IT
LDPC Codes Achieve List Decoding Capacity
Reading time: 2 minute
...
📝 Original Info
- Title: LDPC Codes Achieve List Decoding Capacity
- ArXiv ID: 1909.06430
- Date: 2024-07-11
- Authors: Jonathan Mosheiff, Nicolas Resch, Noga Ron-Zewi, Shashwat Silas, and Mary Wootters
📝 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 $R^*$.📄 Full Content
Reference
This content is AI-processed based on open access ArXiv data.