1 Ocak 2022 Konferans bildirisi Açık Erişim

Nayir, Hasan; Karakoca, Erhan; Gorcin, Ali; Qaraqe, Khalid

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/252745</identifier>
  <creators>
    <creator>
      <creatorName>Nayir, Hasan</creatorName>
      <givenName>Hasan</givenName>
      <familyName>Nayir</familyName>
    </creator>
    <creator>
      <creatorName>Karakoca, Erhan</creatorName>
      <givenName>Erhan</givenName>
      <familyName>Karakoca</familyName>
    </creator>
    <creator>
      <creatorName>Gorcin, Ali</creatorName>
      <givenName>Ali</givenName>
      <familyName>Gorcin</familyName>
    </creator>
    <creator>
      <creatorName>Qaraqe, Khalid</creatorName>
      <givenName>Khalid</givenName>
      <familyName>Qaraqe</familyName>
      <affiliation>Texas A&amp;M Univ Qatar, Dept Elect &amp; Comp Engn, Doha, Qatar</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Hybrid-Field Channel Estimation For Massive Mimo Systems Based On Omp Cascaded Convolutional Autoencoder</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/252745</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/VTC2022-Fall57202.2022.10013010</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Frequency scarcity implies the utilization of higher frequencies for wireless communications; however, spreading loss becomes a dominating issue as the frequency increases to the level of and beyond millimeter waves. To this end, massive multiple-input multiple-output structures introduce mitigation alternatives. However, to make these solutions possible, the channel estimation approach strives to be modified: since Rayleigh distance is very short for conventional systems, the only far-field channel is examined in that context. On the other hand, the implementation of massive antenna arrays in high frequencies increases Rayleigh distance; thus, both near-field and far-field analyses become necessary. Instead of a dual estimation process, it would be effective and efficient to develop hybrid-field channel estimation techniques. Therefore, in this study, a new channel estimation method which is based on convolutional autoencoder (CAE) and orthogonal matching pursuit (OMP) approach, is proposed for hybrid channel estimation. The results indicate that the proposed OMP-CAE method has much better error performance when compared to the conventional OMP algorithm, especially at low signal-to-noise ratio regimes.</description>
  </descriptions>
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