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    <language>eng</language>
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    <pageLast/>
    <pageNumber>6</pageNumber>
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    <type>conferenceobject_ref</type>
    <publisherName>IEEE</publisherName>
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    <completedDate>2019-11-14</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Noise Performance of Orthogonal RF Beamforming for THz Radio Communications</title>
    <parentTitle language="eng">IEEE Computing and Communication Workshop and Conference (CCWC 2019), Las Vegas, USA, 07 - 09 January 2019</parentTitle>
    <identifier type="isbn">978-1-7281-0554-3</identifier>
    <identifier type="doi">10.1109/CCWC.2019.8666546</identifier>
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    <author>
      <firstName>Krishan Kumar</firstName>
      <lastName>Tiwari</lastName>
    </author>
    <submitter>
      <firstName>Heike</firstName>
      <lastName>Wasgien</lastName>
    </submitter>
    <author>
      <firstName>Eckhard</firstName>
      <lastName>Grass</lastName>
    </author>
    <author>
      <firstName>Rolf</firstName>
      <lastName>Kraemer</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
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  <doc>
    <id>25335</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>10</pageFirst>
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    <publisherName>VDE Verlag GmbH</publisherName>
    <publisherPlace>Berlin ; Offenbach</publisherPlace>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-03-05</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Monopulse-Based THz Beam Tracking for Indoor Virtual Reality Applications</title>
    <parentTitle language="deu">Mobilkommunikation : Technologien und Anwendungen : Vorträge der 24. ITG-Fachtagung, 15.-16. Mai 2019 in Osnabrück</parentTitle>
    <identifier type="isbn">978-3-8007-4961-4</identifier>
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    <author>
      <firstName>Krishan Kumar</firstName>
      <lastName>Tiwari</lastName>
    </author>
    <submitter>
      <firstName>Heike</firstName>
      <lastName>Wasgien</lastName>
    </submitter>
    <author>
      <firstName>Vladica</firstName>
      <lastName>Sark</lastName>
    </author>
    <author>
      <firstName>Eckhard</firstName>
      <lastName>Grass</lastName>
    </author>
    <author>
      <firstName>Rolf</firstName>
      <lastName>Kraemer</lastName>
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    <collection role="institutes" number="1222">FG Systeme</collection>
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  <doc>
    <id>25336</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
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    <completedDate>2020-03-05</completedDate>
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    <title language="eng">Beam Entropy of 5G Cellular Millimetre-Wave Channels</title>
    <abstract language="eng">In this paper, we obtain and study typical beam entropy values for millimetre-wave (mm-wave) channel models using the NYUSIM simulator for frequencies up to 100 GHz for the fifth generation (5G) and beyond 5G cellular communication systems. The beam entropy is used to quantify sparse MIMO channel randomness in beamspace. Lower relative beam entropy channels are suitable for memory- assisted statistically-ranked (MarS) and hybrid radio frequency (RF) beam training algorithms. High beam entropies can potentially be advantageous for low overhead secured radio communications by generating cryptographic keys based on the channel randomness in beamspace, especially for sparse multiple-input multiple- output (MIMO) channels. Urban microcell (UMi) and urban macrocell (UMa) cellular scenarios have been investigated in this work for 28, 60, 73, and 100 GHz carrier frequencies and the rural macrocell (RMa) scenario for 3.5 GHz.</abstract>
    <parentTitle language="eng">90th IEEE Vehicular Technology Conference (VTC-Fall 2019), Honolulu, USA, 22 - 25 September 2019</parentTitle>
    <identifier type="isbn">978-1-7281-1220-6</identifier>
    <identifier type="isbn">978-1-7281-1219-0</identifier>
    <identifier type="isbn">978-1-7281-1221-3</identifier>
    <identifier type="doi">10.1109/VTCFall.2019.8891530</identifier>
    <identifier type="issn">2577-2465</identifier>
    <identifier type="issn">1090-3038</identifier>
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    <author>
      <firstName>Krishan Kumar</firstName>
      <lastName>Tiwari</lastName>
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    <submitter>
      <firstName>Heike</firstName>
      <lastName>Wasgien</lastName>
    </submitter>
    <author>
      <firstName>Eckhard</firstName>
      <lastName>Grass</lastName>
    </author>
    <author>
      <firstName>John S.</firstName>
      <lastName>Thompson</lastName>
    </author>
    <author>
      <firstName>Rolf</firstName>
      <lastName>Kraemer</lastName>
    </author>
    <collection role="institutes" number="1222">FG Systeme</collection>
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  <doc>
    <id>26305</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <completedDate>2020-11-12</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Memory-Assisted Statistically-Ranked RF Beam Training Algorithm for Sparse MIMO</title>
    <parentTitle language="eng">2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)</parentTitle>
    <identifier type="doi">10.1109/VTC2020-Spring48590.2020.9129037</identifier>
    <identifier type="isbn">978-1-7281-5207-3</identifier>
    <identifier type="isbn">978-1-7281-4053-7</identifier>
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    <author>
      <firstName>Krishan Kumar</firstName>
      <lastName>Tiwari</lastName>
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    <submitter>
      <firstName>Heike</firstName>
      <lastName>Wasgien</lastName>
    </submitter>
    <author>
      <firstName>Eckhard</firstName>
      <lastName>Grass</lastName>
    </author>
    <author>
      <firstName>John S.</firstName>
      <lastName>Thompson</lastName>
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    <author>
      <firstName>Rolf</firstName>
      <lastName>Kraemer</lastName>
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    <collection role="institutes" number="1222">FG Systeme</collection>
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