Intelligent-Reflecting-Surface-Assisted Multicasting with Joint Beamforming and Phase Adjustment

Abstract

In this paper, a set of transmission schemes are proposed for the delivery of multicast (MC) signals, in which an intelligent reflecting surface (IRS) assists the transmission from an access point (AP) to a set of multicast users. It is known that the large number of IRS reflecting elements have the potential to improve the transmission efficiency by forming an artificial signal path with strong channel gain. However, the joint optimization of the AP beamformer and the phases of the IRS reflecting elements is challenging due to the non-convex nature of the phase elements as well as the high computational complexity required for a large number of elements. A set composed of two AP beamformer schemes and a set with two IRS phase adjustment algorithms are proposed, which are sub-optimal but less computationally demanding. A semi-definite relaxation (SDR)-based scheme is considered along with a least squares (LS) based one for the AP beamformer design. For the IRS phase adjustment, an LS based optimization and a grouping method for the phase elements are suggested. From these two sets, four combinations of overall optimization can be built, and their performances can be compared with their merits and weaknesses revealed. The signal-to-interference-plus-noise power ratio (SINR) performance results are verified in various parameter conditions by simulation.