Conference paper Open Access
Son Le, V.; Abdel Nour, C.; Douillard, C.; Boutillon, E.
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3971729</identifier> <creators> <creator> <creatorName>Son Le, V.</creatorName> <givenName>V.</givenName> <familyName>Son Le</familyName> <affiliation>IMT Atlantique</affiliation> </creator> <creator> <creatorName>Abdel Nour, C.</creatorName> <givenName>C.</givenName> <familyName>Abdel Nour</familyName> <affiliation>IMT Atlantique</affiliation> </creator> <creator> <creatorName>Douillard, C.</creatorName> <givenName>C.</givenName> <familyName>Douillard</familyName> <affiliation>IMT Atlantique</affiliation> </creator> <creator> <creatorName>Boutillon, E.</creatorName> <givenName>E.</givenName> <familyName>Boutillon</familyName> <affiliation>IMT Atlantique</affiliation> </creator> </creators> <titles> <title>A Low-Complexity Dual Trellis Decoding Algorithm for High-Rate Convolutional Codes</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2020</publicationYear> <subjects> <subject>Convolutional codes</subject> <subject>High coding rate</subject> <subject>Dual trellis</subject> <subject>High-throughput decoder</subject> <subject>Low-complexity decoder</subject> <subject>Turbo codes</subject> </subjects> <dates> <date dateType="Issued">2020-08-04</date> </dates> <language>en</language> <resourceType resourceTypeGeneral="Text">Conference paper</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3971729</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3971728</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/epic_h2020</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>Decoding using the dual trellis is considered as a potential technique to increase the throughput of soft-input soft-output decoders for high coding rate convolutional codes. However, the dual Log-MAP algorithm suffers from a high decoding complexity. More specifically, the source of complexity comes from the soft-output unit, which has to handle a high number of extrinsic values in parallel. In this paper, we present a new low-complexity sub-optimal decoding algorithm using the dual trellis, namely the dual Max-Log-MAP algorithm, suited for high coding rate convolutional codes. A complexity analysis and simulation results are provided to compare the dual Max- Log-MAP and the dual Log-MAP algorithms. Despite a minor loss of about 0.2 dB in performance, the dual Max-Log-MAP algorithm significantly reduces the decoder complexity and makes it a first-choice algorithm for high-throughput high-rate decoding of convolutional and turbo codes.</p></description> </descriptions> <fundingReferences> <fundingReference> <funderName>European Commission</funderName> <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier> <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/760150/">760150</awardNumber> <awardTitle>Enabling Practical Wireless Tb/s Communications with Next Generation Channel Coding</awardTitle> </fundingReference> </fundingReferences> </resource>
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