Robust Resource Allocation for Movable Antenna-Enabled MISO Communication Systems with Angular Uncertainties

Movable antenna (MA) technique has emerged as a promising 6G technology due to its flexible deployment and ability to enhance spatial diversity. However, the performance gain depends on the availability of precise angular-domain information. In this paper, we investigate a robust resource allocation (RA) problem for a multiple-input single-output downlink MA-enabled communication system, where angular-domain uncertainties are considered. The RA problem is formulated to maximize the system's total energy efficiency (EE), subject to the maximum transmit power constraint of the base station, the minimum rate constraint of each user, the minimum distance constraints of MAs, and the uncertainty constraints. To deal with the formulated non-convex problem, we first derive an analytical upper bound on the uncertainties of the field response matrix to exactly evaluate the impact of angle errors. Then, an iterative-based robust RA algorithm is proposed by applying the Dinkelbach's method and the block coordinate descent approach. Simulation results demonstrate that the proposed algorithm achieves up to 19.8% higher EE and a 24.9% reduction in outage probability compared to baseline algorithms.