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CHANNEL ESTIMATION AND LOW-COMPLEXITY BEAMFORMING DESIGN FOR PASSIVE INTELLIGENT SURFACE ASSISTED MISO WIRELESS ENERGY TRANSFER
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-3225-6495
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 4659-4663Conference paper, Published paper (Refereed)
Abstract [en]

Usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high energy beamforming (EB) gains. To maximize its realistic utility, we present a novel channel estimation (CE) protocol for PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. Noting the practical limitations of PIS and EH user, all computations are carried out at PB having required active components and radio resources. Using these estimates, near-optimal analytical active and passive EB designs are respectively derived for PB and PIS, that enable efficient PET over a longer duration of coherence block. Nontrivial design insights on relative significance of array size at PIS and PB are also provided. Numerical results validating theoretical claims against the existing benchmarks demonstrate that with sufficient passive elements at PIS, we can achieve desired EB gain with reduced active array size at PB.

Place, publisher, year, edition, pages
IEEE , 2019. p. 4659-4663
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords [en]
Wireless energy harvesting; passive beamforming; antenna array; channel estimation; least-squares; phase shifters
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-160637DOI: 10.1109/ICASSP.2019.8683663ISI: 000482554004179ISBN: 978-1-4799-8131-1 (electronic)OAI: oai:DiVA.org:liu-160637DiVA, id: diva2:1360185
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Note

Funding Agencies|ELLIIT

Available from: 2019-10-11 Created: 2019-10-11 Last updated: 2019-10-11

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf