Maximum Likelihood Decoding for Linear Block Codes Using Grobner Bases
Summary :
New algorithms for the soft-decision and the hard-decision 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.
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- IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.3 pp.643-651
- Publication Date
- 2003/03/01
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- Online ISSN
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- Type of Manuscript
- PAPER
- Category
- Engineering Acoustics
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Daisuke IKEGAMI, Yuichi KAJI, "Maximum Likelihood Decoding for Linear Block Codes Using Grobner Bases" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 3, pp. 643-651, March 2003, doi: .
Abstract: New algorithms for the soft-decision and the hard-decision 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e86-a_3_643/_p
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@ARTICLE{e86-a_3_643,
author={Daisuke IKEGAMI, Yuichi KAJI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Maximum Likelihood Decoding for Linear Block Codes Using Grobner Bases},
year={2003},
volume={E86-A},
number={3},
pages={643-651},
abstract={New algorithms for the soft-decision and the hard-decision 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.},
keywords={},
doi={},
ISSN={},
month={March},}
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TY - JOUR
TI - Maximum Likelihood Decoding for Linear Block Codes Using Grobner Bases
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 643
EP - 651
AU - Daisuke IKEGAMI
AU - Yuichi KAJI
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2003
AB - New algorithms for the soft-decision and the hard-decision 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.
ER -
English
