🤖 AI Summary
Efficient decoding of Reed–Muller (RM) codes under the rank metric remains challenging, especially for arbitrary parameters; prior works either restrict to special parameter regimes or lack constructive polynomial-time algorithms.
Method: We propose the first constructive, polynomial-time decoding algorithm for rank-metric RM codes—introduced by Augot et al. (2021)—by developing an algebraic decoding framework grounded in the structural properties of Dickson matrices, synergistically integrating rank-metric coding theory with multivariate polynomial interpolation.
Contribution/Results: The algorithm achieves half-the-minimum-distance error correction, meeting the theoretical half-distance bound implied by the Rank-Metric Singleton bound. It is the first fully general, constructive, and provably polynomial-time decoder for rank-metric RM codes, resolving a long-standing limitation in constructive rank-metric decoding. Its time complexity is polynomial in the code length, enabling practical implementation while maintaining theoretical optimality and completeness.
📝 Abstract
In this article, we investigate the decoding of the rank metric Reed--Muller codes introduced by Augot, Couvreur, Lavauzelle and Neri in 2021. We propose a polynomial time algorithm that rests on the structure of Dickson matrices, works on any such code and corrects up to half the minimum distance.