Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

• Published in: IEEE transactions on wireless communications Vol. 18; no. 8; pp. 4157 - 4170
• Main Authors: Huang, Chongwen, Zappone, Alessio, Alexandropoulos, George C., Debbah, Merouane, Yuen, Chau
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; alternating maximization; Antennas; Design optimization; Downlink; Energy efficiency; Energy transmission; gradient descent; Hardware; Mathematical programming; multi-user MIMO; non-convex optimization; phase shift; Power consumption; Power demand; Power efficiency; Power management; Reconfigurable intelligent surfaces; Relaying; Relays; Resource allocation; Resource management; sequential fractional programming; Wireless communication; Wireless communications
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2019.2922609

The adoption of a reconfigurable 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.