Optimal Placement of Movable Antennas for Angle-of-Departure Estimation Under User Location Uncertainty

TL;DR

This work addresses AoD estimation with UE location uncertainty using movable antennas at the BS. It derives a Cramér–Rao bound for AoD and develops a region-aware, robust antenna placement strategy that centers precoding on the UE-uncertainty region while enforcing an SCC constraint to limit side lobes. Numerical results show that region-optimized APVs substantially reduce the worst-case CRB compared to fixed configurations (including UFA and UHW), and that the approach adapts effectively as the uncertainty region changes. The findings highlight the practical potential of movable antennas to sustain high angular resolution with lower hardware complexity in next-generation networks.

Abstract

Movable antennas (MA) have gained significant attention in recent years to overcome the limitations of extremely large antenna arrays in terms of cost and power consumption. In this paper, we investigate the use of MA arrays at the base station (BS) for angle-of-departure (AoD) estimation under uncertainty in the user equipment (UE) location. Specifically, we (i) derive the theoretical performance limits through the Cramér-Rao bound (CRB) and (ii) optimize the antenna positions to ensure robust performance within the UE's uncertainty region. Numerical results show that dynamically optimizing antenna placement by explicitly considering the uncertainty region yields superior performance compared to fixed arrays, demonstrating the ability of MA systems to adapt and outperform conventional arrays.

Figures (5)

• Figure 1: Configuration of the MA array.
• Figure 2: Worst-case CRB in degrees for (a) $\mathcal{P}^1$ and (b) $\mathcal{P}^2$.
• Figure 3: $\text{SCC}(\theta_c, \theta, \mathbf{r})$ as a function of $\theta$.
• Figure 4: $\text{CRB}(\mathbf{r} ,\mathbf{F}^{\star}\left(\theta_c,\mathbf{r}\right);\theta)$ as a function of $\theta$.
• Figure 5: Worst-case CRB versus uncertainty region size.