BEAST decoding for block codes

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

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

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Subject classification (UKÄ) – MANDATORY

  • Electrical Engineering, Electronic Engineering, Information Engineering
Original languageEnglish
Title of host publicationITG-Fachbericht
PublisherVDI-Verlag GmBH
Pages173-178
Publication statusPublished - 2004
Publication categoryResearch
Peer-reviewedYes
Event5th International ITG Conference on Source and Channel Coding (SCC´04) - Erlangen, Germany
Duration: 2004 Jan 142004 Jan 16

Publication series

Name
Number181
ISSN (Print)0932-6022

Conference

Conference5th International ITG Conference on Source and Channel Coding (SCC´04)
CountryGermany
CityErlangen
Period2004/01/142004/01/16