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Mathematical Programming Approaches for Decoding of Binary Linear Codes

Akın Tanatmis

Published Jan 1, 2011• 2 citations
OpenAlex

Abstract

In this thesis, we aim at finding appropriate integer programming models and associated solution approaches for the maximum likelihood decoding problem of several binary linear code classes.

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We study an integer programming (IP) based separation approach to find the maximum likelihood (ML) codeword for binary linear codes. An algorithm introduced in Tanatmis et al. is extended and improved with respect to decoding performance without increasing the worst case complexity. This is demonstrated on the LDPC and the BCH code classes. Moreover, we propose an integer programming formulation to calculate the minimum distance of a binary linear code. We exemplarily compute the minimum distance of the (204, 102) LDPC code and the (576, 288) WIMAX code. Using the minimum distance of a code, a new class of valid inequalities is introduced.