Robust Optimization for UAV-Enabled Passive 6-D Movable Antennas With Jitters

Abstract

Passive six-dimensional movable antennas (6DMAs) can be realized by mounting an intelligent reflecting surface (IRS) on an uncrewed aerial vehicle (UAV) and tuning its three-dimensional (3D) deployment and 3D orientation. However, the performance of UAV-enabled passive 6DMAs is highly sensitive to mechanical jitters caused by wind and platform vibration, which can severely limit the communication performance. To resolve this issue, this letter investigates the robust deployment and orientation optimization for UAV-enabled passive 6DMAs, aiming to maximize the worst-case received signal-to-noise ratio (SNR) at a receiver in the presence of bounded jitters. However, this problem is extremely difficult to solve due to its high dimension and worst-case formulation. To tackle this challenge, a particle swarm optimization (PSO) algorithm is first developed, where the sequential quadratic programming (SQP) algorithm is employed to derive the worst-case SNR among all possible jitters for any given 6DMA deployment and orientation. To gain more insights, we further consider a simplified case with pitch jitters only and develop a set of first-order surrogate functions to approximate the received SNR. By this means, closed-form optimal orientation solutions are obtained under mild conditions, which explicitly characterize the impacts of jitters on the communication performance. Numerical results show that the proposed method consistently outperforms the non-robust design that ignores the jitters.