Optimal Movable-Antenna Control for Multi-Path Sensing Guided by Prior AoA Statistic (extended version)

2026-08-10

AI Summary

This work addresses the high overhead and latency incurred by exhaustive full-region scanning in conventional reconfigurable antenna-based multipath sensing. To overcome this limitation, the authors propose an agile sensing framework guided by prior statistics of angle-of-arrival (AoA). For the first time, weak AoA priors are integrated into antenna control, enabling optimization of the antenna array’s three-dimensional orientation via Fisher information analysis. The approach requires only a single directional adjustment followed by two non-collinear linear scans. Combined with maximum a posteriori (MAP) estimation and path interference suppression, it efficiently recovers multipath AoAs and extracts time-of-arrival (ToA) parameters. The method achieves AoA and ToA estimation accuracy approaching that of single-path benchmark performance while substantially reducing control overhead and latency.

Abstract

Multi-path sensing, which aims to extract the geometric attributes of multiple propagation paths, is expected to be a key functionality of 6G. A movable antenna (MA) can enable this functionality by synthesizing an aperture through mechanical motion. However, existing MA-based sensing methods typically rely on exhaustive scanning over the entire movable region, resulting in significant control overhead and sensing latency, which limit their practicality for agile sensing. To address this challenge, this paper develops a prior-guided agile multi-path sensing framework that leverages weak prior angle-of-arrival (AoA) statistics as side information. The proposed framework is built on two key steps. First, the movable plate's three-dimensional orientation is optimized only once to configure a mechanically feasible scan region that enhances path visibility while preserving inter-path discriminability, guided by Fisher information analysis. Second, given the optimal plate orientation, the MA performs only two linear scans, whose non-collinear spatial phase projections are fused with the prior AoA statistics through a maximum a posteriori (MAP)-based estimator to recover the elevation and azimuth AoAs of multiple paths. The estimated AoAs are subsequently used to extract the times-of-arrival (ToAs) by enhancing the target path component while suppressing interference from other paths. With only one orientation adjustment and two linear scans, the proposed framework enables agile multi-path sensing with significantly reduced control overhead and latency, while achieving AoA and ToA estimation accuracy close to the single-path benchmark.

Problem

• multi-path sensing
• movable antenna
• AoA estimation
• sensing latency
• control overhead

Innovation

• movable antenna
• multi-path sensing
• AoA estimation
• prior-guided sensing
• Fisher information