IEICE TRANSACTIONS on Fundamentals
A Soft-Decision Iterative Decoding Algorithm Using a Top-Down and Recursive Minimum Distance Search
Summary :
In this paper, we present a new soft-decision iterative decoding algorithm using an efficient minimum distance search (MDS) algorithm. The proposed MDS algorithm is a top-down and recursive MDS algorithm, which finds a most likely codeword among the codewords at the minimum distance of the code from a given codeword. A search is made in each divided section by a "call by need" from the upper section. As a consequence, the search space and computational complexity are reduced significantly. The simulation results show that the proposed decoding algorithm achieves near error performance to the maximum likelihood decoding for any RM code of length 128 and suboptimal for the (256, 37), (256, 93) and (256, 163) RM codes.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E85-A No.10 pp.2220-2228
- Publication Date
- 2002/10/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Information Theory and Its Applications)
- Category
- Coding Theory
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Jun ASATANI, Kenichi TOMITA, Takuya KOUMOTO, Toyoo TAKATA, Tadao KASAMI, "A Soft-Decision Iterative Decoding Algorithm Using a Top-Down and Recursive Minimum Distance Search" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 10, pp. 2220-2228, October 2002, doi: .
Abstract: In this paper, we present a new soft-decision iterative decoding algorithm using an efficient minimum distance search (MDS) algorithm. The proposed MDS algorithm is a top-down and recursive MDS algorithm, which finds a most likely codeword among the codewords at the minimum distance of the code from a given codeword. A search is made in each divided section by a "call by need" from the upper section. As a consequence, the search space and computational complexity are reduced significantly. The simulation results show that the proposed decoding algorithm achieves near error performance to the maximum likelihood decoding for any RM code of length 128 and suboptimal for the (256, 37), (256, 93) and (256, 163) RM codes.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_10_2220/_p
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@ARTICLE{e85-a_10_2220,
author={Jun ASATANI, Kenichi TOMITA, Takuya KOUMOTO, Toyoo TAKATA, Tadao KASAMI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Soft-Decision Iterative Decoding Algorithm Using a Top-Down and Recursive Minimum Distance Search},
year={2002},
volume={E85-A},
number={10},
pages={2220-2228},
abstract={In this paper, we present a new soft-decision iterative decoding algorithm using an efficient minimum distance search (MDS) algorithm. The proposed MDS algorithm is a top-down and recursive MDS algorithm, which finds a most likely codeword among the codewords at the minimum distance of the code from a given codeword. A search is made in each divided section by a "call by need" from the upper section. As a consequence, the search space and computational complexity are reduced significantly. The simulation results show that the proposed decoding algorithm achieves near error performance to the maximum likelihood decoding for any RM code of length 128 and suboptimal for the (256, 37), (256, 93) and (256, 163) RM codes.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - A Soft-Decision Iterative Decoding Algorithm Using a Top-Down and Recursive Minimum Distance Search
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2220
EP - 2228
AU - Jun ASATANI
AU - Kenichi TOMITA
AU - Takuya KOUMOTO
AU - Toyoo TAKATA
AU - Tadao KASAMI
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2002
AB - In this paper, we present a new soft-decision iterative decoding algorithm using an efficient minimum distance search (MDS) algorithm. The proposed MDS algorithm is a top-down and recursive MDS algorithm, which finds a most likely codeword among the codewords at the minimum distance of the code from a given codeword. A search is made in each divided section by a "call by need" from the upper section. As a consequence, the search space and computational complexity are reduced significantly. The simulation results show that the proposed decoding algorithm achieves near error performance to the maximum likelihood decoding for any RM code of length 128 and suboptimal for the (256, 37), (256, 93) and (256, 163) RM codes.
ER -
English
