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A Soft-Decision Iterative Decoding Algorithm Using a Top-Down and Recursive Minimum Distance Search

Jun ASATANI, Kenichi TOMITA, Takuya KOUMOTO, Toyoo TAKATA, Tadao KASAMI

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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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