Power Optimization for Aerial Intelligent Reflecting Surface-Aided Cell-Free Massive MIMO-Based Wireless Sensor Network

Abstract

Intelligent reflecting surfaces (IRSs) have significant advantages in enhancing the coverage and reducing the deployment cost of wireless networks. This paper studies an aerial IRS- (AIRS-) enhanced cell-free massive multiple-input multiple-output- (MIMO-) based wireless sensor network (WSN) in which multiple access points (APs) serve several sensor users (SUs). Direct links between the APs and SUs are blocked due to occlusion by tall buildings. Hence, we deploy an AIRS to improve the communication quality of the SUs. Our goal is to minimize the total transmit power of all APs under a given minimum signal-to-interference-plus-noise ratio (SINR) requirement. We propose a joint iterative optimization algorithm by designing an active beamforming mechanism at each AP and a passive beamforming mechanism at the AIRS to solve this problem. Simulation results illustrate the good performance of the proposed method.

Nonterrestrial Communications Assisted by Reconfigurable Intelligent Surfaces

“…Second, each RIS element consumes energy, which while being low, may lead to significant power consumption depending on the considered phase resolution for each element. Focusing on multicell systems, the recent work in [141] proposed a design based on ARIS to reduce the power consumption of a free-cell massive MIMO system composed of multiple-antenna GBSs, each serving a group of multiple single-antenna ground sensors.…”