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Weighted Sum-Rate Maximization for Intelligent Reflecting Surface Enhanced Wireless Networks
Univ Elect Sci & Technol China UESTC, Peoples R China.
Univ Elect Sci & Technol China UESTC, Peoples R China.
Univ Elect Sci & Technol China UESTC, Peoples R China.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2019 (English)In: 2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

Intelligent reflecting surface (IRS) is a promising solution to build a programmable wireless environment for future communication systems, in which the reflector elements steer the incident signal in fully customizable ways by passive beamforming. This work focuses on the downlink of an IRS-aided multiuser multiple-input single-output (MISO) system. A practical IRS assumption is considered, in which the incident signal can only be shifted with discrete phase levels. Then, the weighted sum-rate of all users is maximized by joint optimizing the active beamforming at the base-station (BS) and the passive beamforming at the IRS. This non-convex problem is firstly decomposed via Lagrangian dual transform, and then the active and passive beamforming can be optimized alternatingly. In addition, an efficient algorithm with closed-form solutions is proposed for the passive beamforming, which is applicable to both the discrete phase-shift IRS and the continuous phase-shift IRS. Simulation results have verified the effectiveness of the proposed algorithm as compared to different benchmark schemes.

Place, publisher, year, edition, pages
IEEE , 2019.
Series
IEEE Global Communications Conference, ISSN 2334-0983
Keywords [en]
Intelligent reflecting surface (IRS); Reconfigurable Intelligent Surface (RIS); passive radio; multiple-input-multiple-output (MIMO); discrete phase shifts; beamforming
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-168210DOI: 10.1109/GLOBECOM38437.2019.9013288ISI: 000552238601030ISBN: 978-1-7281-0962-6 (electronic)OAI: oai:DiVA.org:liu-168210DiVA, id: diva2:1459416
Conference
IEEE Global Communications Conference (GLOBECOM)
Note

Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China [U1801261, 61631005, 61571100]

Available from: 2020-08-19 Created: 2020-08-19 Last updated: 2020-08-19

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Total: 52 hits
CiteExportLink to record
Permanent link

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