Throughput Optimization in Aerial RIS-Assisted Networks With 3D Imperfect Reflection

In aerial reconfigurable intelligent surface (RIS) assisted networks, parameters of air-to-ground (A2G) channel, such as Rician factors and path-loss exponents, are largely dependent on the three-dimensional (3D) position of RIS-mounted platform, and the inevitable 3D jitter of the aerial platform will cause further phase errors in signal propagation, which results in a 3D imperfect reflection of RIS. However, most existing works only consider invariant channel parameters without jitter during the movement of RIS, which is unrealistic. This paper proposes a more practical autonomous aerial vehicle (AAV)-mounted RIS-assisted communication scheme, where an elevation angle-dependent 3D channel model with AAV jitter is established and the max-min rate problem is effectively solved. Specifically, modeling the Rician factors and the path loss exponents as functions of 3D elevation angles, we reestablish an A2G channel model suitable for 3D reflections containing angular deviations caused by AAV jitter. Furthermore, by rigorously dealing with the difficulties caused by angle dependence, an innovative algorithm is designed for static/mobile RIS-AAV scheme via the joint optimization of base station beamforming, RIS coefficients, and AAV 3D position/trajectory. Additionally, in mobile RIS-AAV scheme, we extra develop a fast algorithm for solving the 0–1 binary integer scheduling factor, which first approximates the solution and then precisely reconstructs it. Simulation results show the robustness of our proposed schemes to angle errors compared with other baselines.