Joint 3D Orientation and Location Optimization for UAV-Mounted Intelligent Reflecting Surface
Changhao Liu, Weidong Mei, Zhi Chen · 2024
Intelligent reflecting surface (IRS) can be mounted on an unmanned aerial vehicle (UAV) to enhance the coverage performance of base stations (BSs) by leveraging the UAV’s flexible and controllable deployment. However, the existing works on UAV-mounted IRSs have mainly focused on their location optimization, which may not unleash their full potential in performance enhancement in light of the UAV’s capability of three-dimensional (3D) posture control. Hence, in this paper, we consider the UAV-mounted IRS-assisted wireless communication from a BS to a remote user, aiming to jointly optimize its location and 3D orientation to maximize the user’s received signal-to-noise ratio (SNR) under the practical angle-dependent signal reflection model. However, this optimization problem is challenging to be optimally solved due to the intricate relationship between the user’s SNR and the IRS’s location and orientation. To tackle this challenge, we first prove that one-dimensional (1D) orientation suffices to achieve the optimal performance, thereby significantly simplifying the optimization problem. Next, we show that for any given IRS’s location, the optimal 1D orientation can be derived in closed form, based on which several useful insights are drawn. Furthermore, in some special cases regarding the UAV/IRS’s altitude and the BS-user distance, we also derive the UAV’s optimal location in closed form. Numerical results validate our theoretical analyses and demonstrate the superiority of the joint location and orientation optimization for the UAV-mounted IRS to its location/orientation optimization only.