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A Deterministic Reduction for the Gap Minimum Distance Problem

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2 Author(s)
Qi Cheng ; Sch. of Comput. Sci., Univ. of Oklahoma, Norman, OK, USA ; Daqing Wan

Determining the minimum distance of a linear code is one of the most important problems in algorithmic coding theory. The exact version of the problem was shown to be NP-complete by Vardy. The gap version of the problem was shown to be NP-hard for any constant factor under a randomized reduction in an earlier work. It was shown in the same paper that the minimum distance problem is not approximable in randomized polynomial time to the factor 2log1-ϵn unless NPRTIME(2polylog(n)). In this paper, we derandomize the reduction and thus prove that there is no deterministic polynomial time algorithm to approximate the minimum distance to any constant factor unless P=NP. We also prove that the minimum distance is not approximable in deterministic polynomial time to the factor 2log1-ϵn unless NPDTIME(2polylog(n)). As the main technical contribution, for any constant 2/3 <; ρ <; 1, we present a deterministic algorithm that given a positive integer s , runs in time poly(s) and constructs a code C of length poly(s) with an explicit Hamming ball of radius ρd(C), such that the projection at the first s coordinates sends the codewords in the ball surjectively onto a linear subspace of dimension s , where d(C) denotes the minimum distance of C. The codes are obtained by concatenating Reed-Solomon codes with Hadamard codes.

Published in:

Information Theory, IEEE Transactions on  (Volume:58 ,  Issue: 11 )

Date of Publication:

Nov. 2012

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