Optimal Active Elements Selection in RIS-Assisted Edge Networks for Improved QoS

Abstract

Reflective intelligent surfaces (RIS) are emerging as a promising solution to alleviate the spectral efficiency challenges and energy consumption issues of the edge networks. RIS is com-prised of programmable, passive, and low-cost electromagnetic elements that assist blockage reduction during signal propagation over wireless channels. The quality-of-service (QoS) challenges over RIS-assisted edge networks can further be improved by the efficient utilization of RIS elements. In particular, in this work, the impacts of RIS elements' amplitude and practical phase-shift model are investigated on the overall network sum rate and required transmit power. Moreover, considering the practical reflection model of RIS, computation of the optimal number of active RIS elements is also performed by putting constraints over QoS conditions. Extensive experimental results demonstrate a significant performance improvement using the proposed method when compared to ideal phase shift and random active elements selection models. © 2022 IEEE.