Aerial RIS-Enhanced Communications: Joint UAV Trajectory, Altitude Control, and Phase Shift Design

TL;DR

The paper addresses beam misalignment in aerial RIS systems caused by UAV tilt and altitude variation by introducing an Euler angles based flight control framework that jointly optimizes ARIS altitude, trajectory, phase shifts, and BS beamforming. It casts the problem as an MDP and solves it with a novel SAC-PER algorithm, while using a water filling plus bisection method for efficient BS beamforming under given ARIS actions. Results show the proposed approach significantly improves sum-rate and yields adaptive trajectories that mitigate tilt induced losses, with about a 14.4% gain over benchmarks. The findings emphasize the importance of co designing UAV dynamics with RIS configuration for robust and scalable ARIS deployments in dynamic environments.

Abstract

Reconfigurable intelligent surface (RIS) has emerged as a pivotal technology for enhancing wireless networks. Compared to terrestrial RIS deployed on building facades, aerial RIS (ARIS) mounted on quadrotor unmanned aerial vehicle (UAV) offers superior flexibility and extended coverage. However, the inevitable tilt and altitude variations of a quadrotor UAV during flight may lead to severe beam misalignment, significantly degrading ARIS's performance. To address this challenge, we propose a Euler angles-based ARIS control scheme that jointly optimizes the altitude and trajectory of the ARIS by leveraging the UAV's dynamic model. Considering the constraints on ARIS flight energy consumption, flight safety, and the transmission power of a base station (BS), we jointly design the ARIS's altitude, trajectory, phase shifts, and BS beamforming to maximize the system sum-rate. Due to the continuous control nature of ARIS flight and the strong coupling among variables, we formulate the problem as a Markov decision process and adopt a soft actor-critic algorithm with prioritized experience replay to learn efficient ARIS control policies. Based on the optimized ARIS configuration, we further employ the water-filling and bisection method to efficiently determine the optimal BS beamforming. Numerical results demonstrate that the proposed algorithm significantly outperforms benchmarks in both convergence and communication performance, achieving approximately 14.4\% improvement in sum-rate. Moreover, in comparison to the fixed-horizontal ARIS scheme, the proposed scheme yields more adaptive trajectories and significantly mitigates performance degradation caused by ARIS tilting, demonstrating strong potential for practical ARIS deployment.

Figures (12)

• Figure 1: The system model of ARIS-assisted communication system with UAV altitude control.
• Figure 2: The altitude variation and definition of ARIS Euler angles.
• Figure 3: The SAC-PER framework.
• Figure 4: The performance of proposed algorithm.
• Figure 5: The trajectories of ARIS for different random seed and height, where $K=8$.