Multiple UAV-Borne IRS-Aided Millimeter Wave Multicast Communications: A Joint Optimization Framework

In this letter, we design a resource allocation algorithm for communications in millimeter wave (mmWave) multicast systems adopting multiple unmanned aerial vehicle (UAV)-borne intelligent reflecting surfaces (IRSs). Considering the effect of blockages of buildings, we jointly optimize the placement of UAVs and the beamforming at the ground base station (BS) and the passive beamforming at the UAV-borne IRSs for maximizing the minimum rate of multiple user clusters. For handling the non-convex optimization problem, firstly, we employ the simulated annealing (SA)-based hybrid particle swarm optimization (HPSO) algorithm to design the deployment of UAVs for maximizing the average minimum achievable rate. Then, we propose a penalty-based block coordinate descent (BCD) algorithm to design the active and passive beamforming for maximizing the instantaneous minimum rate. Simulation results validate the efficiency of our proposed joint optimization framework.