Transmit Power Minimization in Intelligent Reflecting Surfaces-Aided Uplink Communications

Abstract

Employing intelligent reflecting surfaces (IRSs) is emerging as a green alternative to improve the signal quality and suppress interference for massive antenna systems. Specifically, IRS is a planar surface consisting of a large number of low-cost and passive elements each being able to reflect the incident signal independently with an adjustable phase shift. In this paper, we study the power control problem at the user for an IRS-aided uplink system under the quality of service (QoS) constraints. Our goal is to minimize the total transmit power at the user by jointly optimizing the phase shifts of passive elements at the IRS and the receiving beamforming at the BS, subject to the signal-to-noise ratio (SNR) constraint at the user. To solve the resulting non-convex optimization problem, we develop an efficient algorithm, called the manifold-based alternating optimization (M-AO). Simulation results show that the proposed algorithm significantly saved the transmit power.