Maximum-likelihood decoding of Reed-Solomon codes is NP-hard

Maximum-likelihood decoding is one of the central problems in coding theory. It has been known for over 25 years that maximum-likelihood decoding of general linear codes is NP-hard. Nevertheless, it was so far unknown whether maximum-likelihood decoding remains hard for any specific family of codes with nontrivial algebraic structure. In this paper, we prove that maximum-likelihood decoding is NP-hard for the family of Reed-Solomon codes. We moreover show that maximum-likelihood decoding of Reed-Solomon codes remains hard even with unlimited preprocessing, thereby strengthening a result of Bruck and Naor.

[1]  O. Regev Improved inapproximability of lattice and coding problems with preprocessing , 2003, 18th IEEE Annual Conference on Computational Complexity, 2003. Proceedings..

[2]  Elwyn R. Berlekamp,et al.  On the inherent intractability of certain coding problems (Corresp.) , 1978, IEEE Trans. Inf. Theory.

[3]  Antoine Lobstein The hardness of solving subset sum with preprocessing , 1990, IEEE Trans. Inf. Theory.

[4]  Victor Shoup,et al.  New algorithms for finding irreducible polynomials over finite fields , 1988, [Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science.

[5]  Gérard D. Cohen,et al.  Covering Codes , 2005, North-Holland mathematical library.

[6]  W. W. Peterson,et al.  Encoding and error-correction procedures for the Bose-Chaudhuri codes , 1960, IRE Trans. Inf. Theory.

[7]  Christos H. Papadimitriou,et al.  Computational complexity , 1993 .

[8]  Alexander Vardy,et al.  The intractability of computing the minimum distance of a code , 1997, IEEE Trans. Inf. Theory.

[9]  David S. Johnson,et al.  Computers and In stractability: A Guide to the Theory of NP-Completeness. W. H Freeman, San Fran , 1979 .

[10]  Venkatesan Guruswami,et al.  Improved decoding of Reed-Solomon and algebraic-geometry codes , 1999, IEEE Trans. Inf. Theory.

[11]  Elwyn R. Berlekamp,et al.  Algebraic coding theory , 1984, McGraw-Hill series in systems science.

[12]  Madhu Sudan,et al.  Highly Resilient Correctors for Polynomials , 1992, Inf. Process. Lett..

[13]  Moni Naor,et al.  The hardness of decoding linear codes with preprocessing , 1990, IEEE Trans. Inf. Theory.

[14]  Madhu Sudan,et al.  Hardness of approximating the minimum distance of a linear code , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[15]  Madhu Sudan,et al.  Hardness of approximating the minimum distance of a linear code , 1999, IEEE Trans. Inf. Theory.

[16]  Alexander Vardy,et al.  The Parametrized Complexity of Some Fundamental Problems in Coding Theory , 1999, SIAM J. Comput..

[17]  Alexander Vardy,et al.  Algorithmic complexity in coding theory and the minimum distance problem , 1997, STOC '97.

[18]  Richard J. Lipton,et al.  Some connections between nonuniform and uniform complexity classes , 1980, STOC '80.

[19]  Venkatesan Guruswami,et al.  Improved decoding of Reed-Solomon and algebraic-geometric codes , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[20]  Uriel Feige,et al.  The inapproximability of lattice and coding problems with preprocessing , 2004, J. Comput. Syst. Sci..

[21]  Alexander Vardy,et al.  Algebraic soft-decision decoding of Reed-Solomon codes , 2003, IEEE Trans. Inf. Theory.

[22]  Gérard D. Cohen,et al.  Linear Codes with Covering Radius and Codimension , 2001 .

[23]  Jacques Stern,et al.  The hardness of approximate optima in lattices, codes, and systems of linear equations , 1993, Proceedings of 1993 IEEE 34th Annual Foundations of Computer Science.

[24]  Uriel Feige,et al.  The inapproximability of lattice and coding problems with preprocessing , 2002, Proceedings 17th IEEE Annual Conference on Computational Complexity.

[25]  Madhu Sudan,et al.  Decoding of Reed Solomon Codes beyond the Error-Correction Bound , 1997, J. Complex..

[26]  Jacques Stern,et al.  The Hardness of Approximate Optima in Lattices, Codes, and Systems of Linear Equations , 1997, J. Comput. Syst. Sci..

[27]  Ronitt Rubinfeld,et al.  Learning Polynomials with Queries: The Highly Noisy Case , 2000, SIAM J. Discret. Math..