A unified resource optimization framework for multi-area RIS-UAV communication systems.

Abstract

We consider a multi-area user (MAU) communication system assisted by an integrated uncrewed aerial vehicle (UAV) and reconfigurable intelligent surface (RIS). In this RIS-UAV assisted MAU communication system, it is essential to collaboratively optimize the base station (BS)’s power allocation and active beamforming, the RIS's passive beamforming, and the RIS-UAV's trajectory to maximize the achievable system weighted sum rate (WSR). To tackle this challenging joint optimization problem, we design a phase-wise alternating convergent algorithm framework that decomposes it into two main phases: the first phase jointly optimizes the BS power allocation, the BS active beamforming and the RIS passive beamforming, while the second phase optimizes the RIS-UAV trajectory. Adopting the same alternating convergent principle to the first phase, we further break down it into two sub-phases, one for optimizing BS power allocation and the other for jointly optimizing the BS active beamforming and the RIS passive beamforming. The two sub-phases are alternately solved by using a convex optimization method and a manifold optimization algorithm based on fractional programming (FP), respectively. For the second phase, a FP-based successive convex approximation (FP-SCA) trajectory optimization algorithm is proposed, which incorporates distance-based user weights to address the issue of communication service fairness among user areas in the MAU system. Simulation results confirm that our distance-based weighted FP-SCA scheme achieves low complexity, significantly enhances the system WSR performance, and ensures the fairness of communication services.