Decoding rank metric Reed-Muller codes
Alain Couvreur, Rakhi Pratihar
TL;DR
This work addresses decoding rank-metric Reed–Muller codes RM_theta(r, n) over arbitrary Abelian Galois extensions L/K by exploiting G-Dickson matrices. The authors develop a polynomial-time decoder that reconstructs the error theta-polynomial via a majority-voting scheme on the entries of the G-Dickson matrix, enabling correct decoding up to half the minimum distance. The method extends Gabidulin-style decoding from cyclic G to general Abelian G, and provides detailed complexity analyses, including a refinement that achieves essentially a single Gaussian elimination with O~(N^4) base-field operations. The approach broadens the class of efficiently decodable rank-metric codes over infinite fields and offers a framework potentially adaptable to other skew-group-algebra codes. This has implications for cryptography, network coding, and data-storage applications where robust rank-metric decoding over extensions is desirable.
Abstract
In this article, we investigate the decoding of the rank metric Reed--Muller codes introduced by Augot, Couvreur, Lavauzelle and Neri in 2021. These codes are defined from Abelian Galois extensions extending the construction of Gabidulin codes over arbitrary cyclic Galois extensions. We propose a polynomial time algorithm that rests on the structure of Dickson matrices, works on any such code and corrects any error of rank up to half the minimum distance.
