4.7 Article

Wireless Powered Intelligent Reflecting Surfaces for Enhancing Wireless Communications

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 69, Issue 10, Pages 12369-12373

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3011942

Keywords

Array signal processing; Receivers; Scattering; Energy harvesting; Wireless communication; Resource management; Optimization; Energy harvesting; wireless powered transfer; time switching protocol; intelligent reflecting surface

Funding

  1. National Natural Science Foundation of China [61972434, 61977064]
  2. Shenzhen Basic Research Program [JCYJ20190807154009444]
  3. Shenzhen Talent Peacock Plan Program [KQTD2015071715073798]
  4. Fundamental Research Funds for Sun Yat-sen University [19LGPY292]
  5. PCL Future Greater-Bay Area Network Facilities for Largescale Experiments and Applications [LZC0019]
  6. National Research Foundation (NRF), Singapore, under Singapore Energy Market Authority (EMA), Energy Resilience, Singapore [NRF2017EWTEP003-041, NRF2015-NRF-ISF001-2277]
  7. Singapore NRF National Satellite of Excellence, Design Science and Technology for Secure Critical Infrastructure [NSoE DeST-SCI20190007]
  8. A*STAR-NTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing [RGANS1906]
  9. Wallenberg AI, Autonomous Systems and Software Program and Nanyang Technological University (WASP/NTU) [M4082187 (4080)]
  10. NTU-WeBank JRI [NWJ-2020-004]

Ask authors/readers for more resources

Recently, the intelligent reflecting surface (IRS) has become a promising technology for energy-, and spectrum-efficient communications by reconfiguring the radio environment. In this paper, we considermultipleinput single-output (MISO) transmissions from a multi-antenna access point (AP) to a receiver, assisted by a practical IRS with a power budget constraint. The IRS can work in energy harvesting, and signal reflecting phases. It firstly harvests RF energy from the AP's signal beamforming, and then uses it to sustain its operations in the signal reflecting phase. We aim to characterize themaximum capacity by optimizing the AP's transmit beamforming, the IRS's time allocation in two operational phases, and the IRS's passive beamforming to enhance the information rate. To solve the non-convex maximization problem, we exploit its structural properties, and decompose it into two sub-problems in two phases. The IRS's phase shift optimization in the reflecting phase follows a conventional passive beamforming problem to maximize the received signal power. In the energy harvesting phase, the IRS's time allocation, and the AP's transmit beamforming are jointly optimized using monotonic optimization. Simulation results verify the effectiveness of the proposed algorithm.

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