Balanced Reed-Solomon Codes

TL;DR

This paper presents an explicit method to transform Reed-Solomon codes into sparse and balanced generator matrices, optimizing computational load distribution while maintaining error correction capabilities.

Contribution

It provides a constructive approach to obtain sparse, balanced generator matrices for Reed-Solomon codes, enabling efficient decoding and load balancing.

Findings

Existence of sparse, balanced generator matrices for Reed-Solomon codes.

Transformation method applicable for all parameters where (k/n)*(n-k+1) is integer.

Enhanced efficiency in error correction and computational load distribution.

Abstract

We consider the problem of constructing linear Maximum Distance Separable (MDS) error-correcting codes with generator matrices that are sparsest and balanced. In this context, sparsest means that every row has the least possible number of non-zero entries, and balanced means that every column contains the same number of non-zero entries. Codes with this structure minimize the maximal computation time of computing any code symbol, a property that is appealing to systems where computational load-balancing is critical. The problem was studied before by Dau et al. where it was shown that there always exists an MDS code over a sufficiently large field such that its generator matrix is both sparsest and balanced. However, the construction is not explicit and more importantly, the resulting MDS codes do not lend themselves to efficient error correction. With an eye towards explicit constructions with efficient decoding, we show in this paper that the generator matrix of a cyclic Reed-Solomon code of length $n$ and dimension $k$ can always be transformed to one that is both sparsest and balanced, for all parameters $n$ and $k$ where $\frac{k}{n}(n - k + 1)$ is an integer.