Title :
Mathematical Programming Decoding of Binary Linear Codes: Theory and Algorithms
Author :
Michael Helmling;Stefan Ruzika;Akın Tanatmis
Author_Institution :
Department of Mathematics, University of Kaiserslautern, Kaiserslautern, Germany
Abstract :
Mathematical programming is a branch of applied mathematics and has recently been used to derive new decoding approaches, challenging established but often heuristic algorithms based on iterative message passing. Concepts from mathematical programming used in the context of decoding include linear, integer, and nonlinear programming, network flows, notions of duality as well as matroid and polyhedral theory. This paper reviews and categorizes decoding methods based on mathematical programming approaches for binary linear codes over binary-input memoryless symmetric channels.
Keywords :
"Linear code","Vectors","Maximum likelihood decoding","Iterative decoding","Complexity theory"
Journal_Title :
IEEE Transactions on Information Theory
DOI :
10.1109/TIT.2012.2191697