A Groebner-bases approach to syndrome-based fast Chase decoding of Reed--Solomon codes
Abstract
We present a simple syndrome-based fast Chase decoding algorithm for Reed--Solomon (RS) codes. Such an algorithm was initially presented by Wu (IEEE Trans. IT, Jan. 2012), building on properties of the Berlekamp--Massey (BM) algorithm. Wu devised a fast polynomial-update algorithm to construct the error-locator polynomial (ELP) as the solution of a certain linear-feedback shift register (LFSR) synthesis problem. This results in a conceptually complicated algorithm, divided into subtly different cases. Moreover, Wu's polynomial-update algorithm is not immediately suitable for working with vectors of evaluations. Therefore, complicated modifications were required in order to achieve a true "one-pass" Chase decoding algorithm, that is, a Chase decoding algorithm requiring operations per modified coordinate, where is the RS code length. The main result of the current paper is a conceptually simple syndrome-based fast Chase decoding of RS codes. Instead of developing a theory from scratch, we use the well-established theory of Groebner bases for modules over (where is the finite field of elements, for a prime power). The basic observation is that instead of Wu's LFSR synthesis problem, it is much simpler to consider "the right" minimization problem over a module. The solution to this minimization problem is a simple polynomial-update algorithm that avoids syndrome updates and works seamlessly with vectors of evaluations. As a result, we obtain a conceptually simple algorithm for one-pass Chase decoding of RS codes. Our algorithm is general enough to work with any algorithm that finds a Groebner basis for the solution module of the key equation as the initial algorithm (including the Euclidean algorithm), and it is not tied only to the BM algorithm.
Keywords
Cite
@article{arxiv.2008.01796,
title = {A Groebner-bases approach to syndrome-based fast Chase decoding of Reed--Solomon codes},
author = {Yaron Shany and Amit Berman},
journal= {arXiv preprint arXiv:2008.01796},
year = {2022}
}
Comments
Added Algorithm C, accepted for publication