Adaptive Beam Alignment and Optimization for IRS-Aided High-Speed UAV Communications

Abstract

In the unmanned aerial vehicle (UAV) enabled wireless communication system, the rapid channel change caused by high-speed UAV may cause the beam misalignment problem. It is a challenge to fast establish and maintain the communications link between UAV and ground base stations. To address this challenge, an IRS-aided high-speed UAV adaptive beam alignment (IRS-UAV-ABA) scheme utilizing double-layer long short-term memory (DL-LSTM) spatial angle prediction model is proposed to improve the effectiveness and reliability of the UAV communication. Firstly, DL-LSTM enabled spatial angle prediction is modeled to facilitate the calculation of the beam coverage adapted to the UAV real-time flight trajectory. Secondly, the non-convex optimization problem for maximizing the received signal-to-noise ratio of moving UAV is formulated to obtain the suboptimal solutions of the BS’ beamforming vector and the IRS’ phase shift matrix. Finally, with the aforementioned beamforming vectors, the phase shift matrix and the adaptive beam coverage, the adaptive dual-beams alignment from BS to UAV and from IRS to UAV can be achieved by the proposed DL-LSTM-enabled IRS-UAV-ABA algorithm. Simulation results verify that the proposed scheme not only can effectively avoid the beam misalignment caused by the mobility and perturbation of UAV, but also has superior spectrum efficiency and stable beamforming gain.