4.7 Article

Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 18, Issue 8, Pages 4157-4170

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2019.2922609

Keywords

Reconfigurable intelligent surfaces; multi-user MIMO; energy efficiency; phase shift; non-convex optimization; alternating maximization; gradient descent; sequential fractional programming

Funding

  1. H2020 Marie Sklodowska-Curie Actions (MSCA) Individual Fellowships (IF) BESMART [749336]
  2. H2020-ERC PoC-CacheMire [727682]
  3. MIT-SUTD International design center
  4. National Natural Science Foundation of China (NSFC) [NSFC 61750110529]
  5. Partenariats Hubert Curien (PHC) Merlion Ph.D. program [913888J]
  6. Marie Curie Actions (MSCA) [749336] Funding Source: Marie Curie Actions (MSCA)
  7. European Research Council (ERC) [727682] Funding Source: European Research Council (ERC)

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The adoption of a reconfigurahle intelligent surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to 300% higher energy efficiency in comparison with the use of regular multi-antenna amplify-and-forward relaying.

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