Abstract

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.

Keywords

Computer scienceBase stationFractional programmingTransmitter power outputTelecommunications linkMathematical optimizationWirelessGradient descentResource allocationMaximizationEfficient energy useEnergy consumptionOptimization problemEnergy (signal processing)AlgorithmComputer networkTelecommunicationsElectrical engineeringMathematicsNonlinear programmingArtificial intelligenceEngineeringChannel (broadcasting)Transmitter

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Year
2018
Type
article
Citations
3473
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Chongwen Huang, Alessio Zappone, George C. Alexandropoulos et al. (2018). Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication. arXiv (Cornell University) . https://doi.org/10.1109/twc.2019.2922609

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DOI
10.1109/twc.2019.2922609