# Optimizations with Intelligent Reflecting Surfaces (IRSs) in 6G Wireless Networks: Power Control, Quality of Service, Max-Min Fair Beamforming for Unicast, Broadcast, and Multicast with Multi-antenna Mobile Users and Multiple IRSs

## TL;DR

This paper develops optimization algorithms for power control, beamforming, and phase shifts in IRS-assisted 6G wireless networks, addressing unicast, broadcast, and multicast traffic with multi-antenna users and multiple IRSs.

## Contribution

It introduces the first joint optimization framework for power control and beamforming in IRS-assisted networks considering max-min fairness and multiple traffic patterns.

## Key findings

- Proposed efficient algorithms for joint beamforming and IRS phase shift design.
- Extended optimization to multi-antenna users and multiple IRSs.
- Achieved improved QoS and fairness in simulated IRS-assisted 6G scenarios.

## Abstract

Intelligent reflecting surfaces (IRSs) have received much attention recently and are envisioned to promote 6G communication networks. In this paper, for wireless communications aided by IRS units, we formulate optimization problems for power control under quality of service (QoS) and max-min fair QoS under three kinds of traffic patterns from a base station (BS) to mobile users (MUs): unicast, broadcast, and multicast. The optimizations are achieved by jointly designing the transmit beamforming of the BS and the phase shift matrix of the IRS. For power control under QoS, existing IRS studies in the literature address only the unicast setting, whereas no IRS work has considered max-min fair QoS. Furthermore, we extend our above optimization studies to the novel settings of multi-antenna mobile users or/and multiple intelligent reflecting surfaces. For all the above optimizations, we provide detailed analyses to propose efficient algorithms. To summarize, our paper presents a comprehensive study of optimization problems involving power control, QoS, and fairness in wireless networks enhanced by IRSs.