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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/4977

Title: Maximum likelihood decoding for linear block codes using Grobner bases
Authors: Ikegami, Daisuke
Kaji, Yuichi
Issue Date: 1-Mar-2003
Publisher: Institute of Electronics, Information and Communication Engineers
Journal Title: IEICE transactions on fundamentals of electronics, communications and computer sciences
Volume: E86-A
Issue: 3
Start page: 643
End page: 651
Abstract: New algorithms for the soft-derision and the hard-derision maximum likelihood decoding (MLD) for binary linear block codes are proposed. It has been widely known that both MLD can be regarded as an integer programming with binary arithmetic conditions. Recently, Conti and Traverso have proposed an efficient algorithm which uses Grobner bases to solve integer programming with ordinary integer arithmetic conditions. In this paper, the Conti-Traverso algorithm is extended to solve integer programming with modulo arithmetic conditions. We also show how to transform the soft-decision and the hard-decision MLD to integer programming for which the extended Conti-Traverso algorithm is applicable.
URI: http://hdl.handle.net/10061/4977
URL: http://search.ieice.org
ISSN: 0916-8508
Rights: Copyright (C)2003 IEICE
Text Version: publisher
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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