Joint Robust Beamforming and Orientation Optimizing for ARIS-aided Communication with ARIS Location Uncertainty

This letter considers an aerial reconfigurable intelligent surface (ARIS)-aided communication system in which the RIS is installed on aerial platforms to provide stable communication services instead of the traditional terrestrial RIS. However, obtaining perfect information about the ARIS location is practically challenging, which can result in performance degradation. This letter presents a robust optimization problem of beamforming and ARIS orientation to minimize transmit power subject to constraints such as rate disruption and ARIS location uncertainty. Particularly, the semi-definite relaxation (SDR) and Bernstein-type inequality are adopted to solve the non-convex constraints in the problem while a rotation matrix represents the ARIS orientation, and we adopt the optimization principle on the manifold to deal with the inherent overdetermination of rotation matrices and to reduce computational complexity. The simulation results verify the robustness and effectiveness of the proposed algorithm.