Movable-Antenna Wireless Sensing: Trajectory Optimization and Performance Limit

Abstract

In this paper, we present a new wireless sensing system utilizing a movable antenna (MA) that continuously moves and receives sensing signals to enhance sensing performance over the conventional fixed-position antenna (FPA) sensing. We show that the angle estimation performance is fundamentally determined by the MA trajectory, and derive the Cramér-Rao bound (CRB) of the mean square error (MSE) for angle-ofarrival (AoA) estimation as a function of the trajectory for two-dimensional (2D) antenna movement. We aim to achieve the minimum of maximum (min-max) CRBs of estimation MSE for the two AoAs with respect to the horizontal and vertical axes. To this end, we design an efficient alternating optimization algorithm that iteratively updates the MA's horizontal or vertical coordinates with the other being fixed, yielding a locally optimal trajectory. Numerical results show that the proposed 2D MAbased sensing schemes significantly reduce both the CRB and actual AoA estimation MSE compared to conventional FPA-based sensing with uniform planar arrays (UPAs) as well as various benchmark MA trajectories.