Optimal rate list decoding via derivative codes

  • Authors:
  • Venkatesan Guruswami;Carol Wang

  • Affiliations:
  • Computer Science Department, Carnegie Mellon University, Pittsburgh, PA;Computer Science Department, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • APPROX'11/RANDOM'11 Proceedings of the 14th international workshop and 15th international conference on Approximation, randomization, and combinatorial optimization: algorithms and techniques
  • Year:
  • 2011

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Abstract

The classical family of [n, k]q Reed-Solomon codes over a field Fq consist of the evaluations of polynomials f ∈ Fq[X] of degree k at n distinct field elements. In this work, we consider a closely related family of codes, called (order m) derivative codes and defined over fields of large characteristic, which consist of the evaluations of f as well as its first m - 1 formal derivatives at n distinct field elements. For large enough m, we show that these codes can be list-decoded in polynomial time from an error fraction approaching 1 - R, where R = k/(nm) is the rate of the code. This gives an alternate construction to folded Reed-Solomon codes for achieving the optimal trade-off between rate and list error-correction radius. Our decoding algorithm is linear-algebraic, and involves solving a linear system to interpolate a multivariate polynomial, and then solving another structured linear system to retrieve the list of candidate polynomials f. The algorithm for derivative codes offers some advantages compared to a similar one for folded Reed-Solomon codes in terms of efficient unique decoding in the presence of side information.