Conference paper Open Access

# A Low-Complexity Dual Trellis Decoding Algorithm for High-Rate Convolutional Codes

Son Le, V.; Abdel Nour, C.; Douillard, C.; Boutillon, E.

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<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="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;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.&lt;/p&gt;</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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