Random Reed-Solomon Codes Achieve List-Decoding Capacity With Linear-Sized Alphabets

TL;DR

This paper proves that Reed-Solomon codes can achieve list-decoding capacity over linear-sized alphabets, resolving a key open problem and improving understanding of their decoding capabilities.

Contribution

It demonstrates that Reed-Solomon codes are list-decodable to capacity over linear fields, and shows random linear codes also achieve capacity with optimal list-size and near-optimal alphabet size.

Findings

Reed-Solomon codes are list-decodable to capacity over O(n) field size.

Random linear codes achieve list-decoding capacity with O(1/ε) list-size.

List-decoding up to capacity with optimal list-size was previously unknown for linear codes.

Abstract

Reed-Solomon codes are a classic family of error-correcting codes consisting of evaluations of low-degree polynomials over a finite field on some sequence of distinct field elements. They are widely known for their optimal unique-decoding capabilities, but their list-decoding capabilities are not fully understood. Given the prevalence of Reed-Solomon codes, a fundamental question in coding theory is determining if Reed-Solomon codes can optimally achieve list-decoding capacity. A recent breakthrough by Brakensiek, Gopi, and Makam established that Reed-Solomon codes are combinatorially list-decodable all the way to capacity. However, their results hold for randomly-punctured Reed-Solomon codes over an exponentially large field size $2^{O(n)}$, where $n$ is the block length of the code. A natural question is whether Reed-Solomon codes can still achieve capacity over smaller fields. We show that Reed-Solomon codes are list-decodable to capacity with linear field size $O(n)$, which is evidently optimal up to a constant factor. Our techniques also show that random linear codes are list-decodable up to capacity with optimal list-size $O(1/\varepsilon)$ and near-optimal alphabet size $2^{O(1/\varepsilon^2)}$, where $\varepsilon$ is the gap to capacity. As far as we are aware, list-decoding up to capacity with optimal list-size $O(1/\varepsilon)$ was not known to be achievable with any linear code over a constant alphabet size (even non-constructively), and it was also not known to be achievable for random linear codes over any alphabet size. With our proof, which maintains a hypergraph perspective of the list-decoding problem, we include an alternate presentation of ideas from Brakensiek, Gopi, and Makam that more directly connects the list-decoding problem to the GM-MDS theorem via a hypergraph orientation theorem.