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On Pseudocodewords and Decision Regions of Linear Programming Decoding of HDPC Codes | IEEE Journals & Magazine | IEEE Xplore

On Pseudocodewords and Decision Regions of Linear Programming Decoding of HDPC Codes


Abstract:

In this paper we explore the decision regions of Linear Programming (LP) decoding. We compare the decision regions of an LP decoder, a Belief Propagation (BP) decoder and...Show More

Abstract:

In this paper we explore the decision regions of Linear Programming (LP) decoding. We compare the decision regions of an LP decoder, a Belief Propagation (BP) decoder and the optimal Maximum Likelihood (ML) decoder. We study the effect of minimal-weight pseudocodewords on LP decoding. We present global optimization as a method for finding the minimal pseudoweight of a given code as well as the number of minimal-weight generators. We present a complete pseudoweight distribution for the [24, 12, 8] extended Golay code, and provide justifications of why the pseudoweight distribution alone cannot be used for obtaining a tight upper bound on the error probability.
Published in: IEEE Transactions on Communications ( Volume: 60, Issue: 4, April 2012)
Page(s): 963 - 971
Date of Publication: 14 February 2012

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I. Introduction

The behavior of the BP [1] decoder for the case of finite-length codes does not have simple characteristics, and can be very hard to predict. Linear programming is a well-studied discipline that provides efficient analysis tools. The relationship between linear programming decoding [2] and BP decoding was observed and characterized [3], and the decision regions of these decoders are suggested to be tightly related. The LP decoder receives the channel likelihood ratios which define an objective function, for which it finds an optimal solution that satisfies a set of constraints. These constraints are inequalities arisen from a given parity -check matrix and form a polytope, also known as the fundamental polytope [4]. The fundamental polytope is a relaxation of the codewords polytope. It has a clear geometrical representation which is well-suited for finite-length analysis. The vertices of the fundamental polytope are every codeword, but also some non-codewords pseudocodewords [2]. The fundamental cone [4] is the conic hull of the fundamental polytope. It has a vertex in the origin, and its edges are also referred to as minimal pseudo-codewords [4] or generators [5]. The fundamental cone has a more compact representation than the fundamental polytope, and it is sufficient to consider the fundamental cone for evaluating the performance of the LP decoder [2], [4], [5].

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