Joint Precoding, Passive Beamforming, and 3-D Trajectories Optimization for UAV-RISs-Assisted Systems With Statistical CSI

Abstract

The combination of uncrewed aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) forms a cooperative framework that exploits the mutual advantages of both technologies. In this work, multiple RISs mounted on fixed-wing UAVs are adopted to adaptively reconfigure the transmission environments of communications. Given the practical significance of the proposed research, this study incorporates the phase-dependent amplitude response under realistic discrete phase shifts in RISs and accounts for statistical channel state information (CSI). In view of the practical designs of fixed-wing UAVs’ mobilities, the flight turning and pitch angles are considered in it to enhance the application value. Specifically, an optimization framework is designed to maximize the average data rate under statistical CSI over the UAVs’ flight duration by simultaneously optimizing BS’s transmit precoding, practical phase shifts of RISs, UAVs’ 3D trajectories, velocities, accelerations, and flight timeslot durations. To address this highly coupled and non-convex problem, an algorithm based on penalty dual decomposition (PDD) is introduced, incorporating weighted minimum mean square error (WMMSE) and successive convex approximation (SCA). The non-convex objective function is initially converted into a more manageable form by using WMMSE and analysis under statistical CSI. Then, variables are decoupled via auxiliary variables and alternately optimized in the inner iteration process, while operating the update of penalty and dual factors in the outer iteration process. Simulation results demonstrate the effectiveness of the proposed method.