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Soft-output BEAST decoding with application to product Codes

Loncar, Maja LU ; Johannesson, Rolf LU ; Bocharova, Irina LU and Kudryashov, Boris LU (2008) In IEEE Transactions on Information Theory 54(3). p.1036-1049
Abstract
A Bidirectional Efficient Algorithm for Searching code Trees (BEAST) is proposed for efficient soft-output decoding of block codes and concatenated block codes. BEAST operates on trees corresponding to the minimal trellis of a block code and finds a list of the most probable codewords. The complexity of the BEAST search is significantly lower than the complexity of trellis-based algorithms, such as the Viterbi algorithm and its list-generalizations. The outputs of BEAST, a list of best codewords and their metrics, are used to obtain approximate a posteriori reliabilities of the transmitted symbols, yielding a soft-input soft-output (SISO) symbol decoder referred to as the BEAST-APP decoder. This decoder is employed as a component decoder... (More)
A Bidirectional Efficient Algorithm for Searching code Trees (BEAST) is proposed for efficient soft-output decoding of block codes and concatenated block codes. BEAST operates on trees corresponding to the minimal trellis of a block code and finds a list of the most probable codewords. The complexity of the BEAST search is significantly lower than the complexity of trellis-based algorithms, such as the Viterbi algorithm and its list-generalizations. The outputs of BEAST, a list of best codewords and their metrics, are used to obtain approximate a posteriori reliabilities of the transmitted symbols, yielding a soft-input soft-output (SISO) symbol decoder referred to as the BEAST-APP decoder. This decoder is employed as a component decoder in iterative schemes for decoding of product and incomplete product codes. Its performance and convergence behavior are investigated using EXIT charts and compared to existing

decoding schemes. It is shown that the BEAST-APP decoder achieves performances close to the BCJR decoder with a substantially lower computational complexity. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
block turbo codes, list decoding, product codes, BEAST, soft-input soft-output (SISO) decoding
in
IEEE Transactions on Information Theory
volume
54
issue
3
pages
1036 - 1049
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • WOS:000253602200006
  • Scopus:40949156723
ISSN
0018-9448
DOI
10.1109/TIT.2007.915971
language
English
LU publication?
yes
id
3cfe5457-1446-4b25-82a0-27e4fe8636df (old id 959898)
date added to LUP
2008-01-28 13:01:21
date last changed
2016-10-13 04:31:56
@misc{3cfe5457-1446-4b25-82a0-27e4fe8636df,
  abstract     = {A Bidirectional Efficient Algorithm for Searching code Trees (BEAST) is proposed for efficient soft-output decoding of block codes and concatenated block codes. BEAST operates on trees corresponding to the minimal trellis of a block code and finds a list of the most probable codewords. The complexity of the BEAST search is significantly lower than the complexity of trellis-based algorithms, such as the Viterbi algorithm and its list-generalizations. The outputs of BEAST, a list of best codewords and their metrics, are used to obtain approximate a posteriori reliabilities of the transmitted symbols, yielding a soft-input soft-output (SISO) symbol decoder referred to as the BEAST-APP decoder. This decoder is employed as a component decoder in iterative schemes for decoding of product and incomplete product codes. Its performance and convergence behavior are investigated using EXIT charts and compared to existing<br/><br>
decoding schemes. It is shown that the BEAST-APP decoder achieves performances close to the BCJR decoder with a substantially lower computational complexity.},
  author       = {Loncar, Maja and Johannesson, Rolf and Bocharova, Irina and Kudryashov, Boris},
  issn         = {0018-9448},
  keyword      = {block turbo codes,list decoding,product codes,BEAST,soft-input soft-output (SISO) decoding},
  language     = {eng},
  number       = {3},
  pages        = {1036--1049},
  publisher    = {ARRAY(0xb705a18)},
  series       = {IEEE Transactions on Information Theory},
  title        = {Soft-output BEAST decoding with application to product Codes},
  url          = {http://dx.doi.org/10.1109/TIT.2007.915971},
  volume       = {54},
  year         = {2008},
}