Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting

In this paper, we examine the use of intelligent reflective surface (IRS) to reconfigure the wireless propagation environment which assists the physical-layer multicast transmission with simple single-antenna radios in the network. Different phase-shift strategies are employed to adjust the reflection of the IRS. On the one hand, the max-min criterion is utilized to enhance the achievable rate of the receive nodes inside the multicast-target group. On the other hand, for the nodes outside the multicast-target group in the same network, we take advantage of another min-max criterion to let them all be less interfered with by the specific multicast communication. Multiobjective optimization is then set to reveal the compromises between the effect on the nodes of the two different groups. Simulation results show that the proposed IRS-aided physical-layer multicasting can fulfill the above-stated task, and can let the nodes in either group gain better results.