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="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">&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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