Multi-objective optimization for active IRS-aided multi-group multicast systems with energy harvesting, integrated sensing and communication

In this paper, we utilize an active intelligent reflecting surface (IRS) to assist wireless systems with multiple functionalities, including multi-group (MG) multicast (MC) transmission, integrated sensing and communication (ISAC) and wireless energy harvesting. Specifically, a multi-antenna base station (BS) simultaneously transmits communication signals to MG MC users and sensing signals towards targets, while other users can harvest energy from the received radio frequency signals. We formulate the joint design of the BS transmit precoders (TPs) and the IRS reflection coefficients (RCs) as multi-objective optimization problems (MOOPs) in which the objective functions of the sum rate maximization (SRM) and sum harvested energy maximization (SHEM) are considered under the constraints of transmit power at the BS, amplitude and power amplifications at the active IRS, minimum achievable rate of communication users (CUs), minimum harvested energy of energy harvesting users (EHUs), and beamforming pattern similarity for sensing. To tackle the nonconvexity characteristics of the formulated design problems, we leverage alternating optimization (AO) frameworks to decompose the original problems into subproblems. In the subproblems, we seek appropriate surrogate functions by following majorization–minimization (MaMi) techniques to convert the subproblems into convex ones. Then, iterative algorithms are developed to obtain the optimal BS TPs and IRS RCs. The numerical simulations are carried out to validate the effectiveness of the proposed methods. The numerical results also reveal useful insights in the tradeoffs between the performance metrics and demonstrate the superior performance of systems with an active IRS in comparison with those without an IRS or with a passive IRS.