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BEAST decoding for block codes

Bocharova, Irina LU ; Johannesson, Rolf LU ; Kudryashov, Boris LU and Loncar, Maja LU (2004) 5th International ITG Conference on Source and Channel Coding (SCC) In ITG-Fachbericht p.173-178
Abstract
BEAST is a Bidirectional Efficient Algorithm for Searching code Trees. In this paper, it is used for decoding block codes over the additive white Gaussian noise (AWGN) channel. If no constraints are imposed on the decoding complexity (in terms of the number of visited nodes during the search), BEAST performs maximum-likelihood (ML) decoding. At the cost of a negligible performance degradation, BEAST can be constrained to perform almost-ML decoding with significantly reduced complexity. The benchmark for the complexity assessment is the number of nodes visited by the Viterbi algorithm operating on the minimal trellis of the code. The decoding complexity depends on the trellis structure of a given code, which is illustrated by three... (More)
BEAST is a Bidirectional Efficient Algorithm for Searching code Trees. In this paper, it is used for decoding block codes over the additive white Gaussian noise (AWGN) channel. If no constraints are imposed on the decoding complexity (in terms of the number of visited nodes during the search), BEAST performs maximum-likelihood (ML) decoding. At the cost of a negligible performance degradation, BEAST can be constrained to perform almost-ML decoding with significantly reduced complexity. The benchmark for the complexity assessment is the number of nodes visited by the Viterbi algorithm operating on the minimal trellis of the code. The decoding complexity depends on the trellis structure of a given code, which is illustrated by three different forms of the generator matrix for the (24, 12, 8) Golay code. Simulation results are also presented for two other codes (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
ITG-Fachbericht
issue
181
pages
173 - 178
publisher
VDI-Verlag GmBH
conference name
5th International ITG Conference on Source and Channel Coding (SCC)
ISSN
0932-6022
language
English
LU publication?
yes
id
e47a1707-7f81-453d-9704-0cf0ff4cc354 (old id 629009)
date added to LUP
2007-12-05 15:08:49
date last changed
2016-07-06 13:00:11
@inproceedings{e47a1707-7f81-453d-9704-0cf0ff4cc354,
  abstract     = {BEAST is a Bidirectional Efficient Algorithm for Searching code Trees. In this paper, it is used for decoding block codes over the additive white Gaussian noise (AWGN) channel. If no constraints are imposed on the decoding complexity (in terms of the number of visited nodes during the search), BEAST performs maximum-likelihood (ML) decoding. At the cost of a negligible performance degradation, BEAST can be constrained to perform almost-ML decoding with significantly reduced complexity. The benchmark for the complexity assessment is the number of nodes visited by the Viterbi algorithm operating on the minimal trellis of the code. The decoding complexity depends on the trellis structure of a given code, which is illustrated by three different forms of the generator matrix for the (24, 12, 8) Golay code. Simulation results are also presented for two other codes},
  author       = {Bocharova, Irina and Johannesson, Rolf and Kudryashov, Boris and Loncar, Maja},
  booktitle    = {ITG-Fachbericht},
  issn         = {0932-6022},
  language     = {eng},
  number       = {181},
  pages        = {173--178},
  publisher    = {VDI-Verlag GmBH},
  title        = {BEAST decoding for block codes},
  year         = {2004},
}