Prior-Guided Movable Antenna Control for Agile Multi-Path Sensing (extended version)

2026-04-13

AI Summary

This work addresses the high control overhead and latency of conventional mobile antenna-based multipath sensing for 6G agile perception, which typically relies on exhaustive full-region scanning. To overcome these limitations, the authors propose a prior-guided agile multipath sensing framework that, for the first time, incorporates weak angular-of-arrival (AoA) prior statistics into the antenna control strategy. By leveraging Fisher information–based 3D beamforming optimization and two predefined linear scans, combined with maximum a posteriori (MAP) estimation and synthetic aperture signal processing, the framework achieves accurate AoA estimation with only a single directional adjustment. Experimental results demonstrate that the proposed method significantly reduces control complexity and sensing latency while attaining AoA estimation accuracy approaching that of the single-path benchmark, thereby confirming its efficiency and practicality.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: State Estimation

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Agentic search
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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 creating a synthetic aperture through sequential mechanical motion. However, existing MA-based sensing methods typically rely on exhaustive scanning over the entire movable plate, resulting in significant control overhead and sensing latency, which limits 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 comprises two steps. First, the movable plate's three-dimensional orientation is optimized only once to maximize path visibility while preserving path discriminability, both induced from Fisher information analysis. Second, only two predetermined linear MA scans are made on the tilted plate to estimate the elevation and azimuth AoAs from the resulting sequence of received signals. By incorporating the prior AoA statistics, a maximum a posteriori (MAP)-based AoA estimation algorithm is developed. With only one orientation control and two linear scans, the proposed framework enables agile multi-path sensing with significantly reduced control overhead and latency, while achieving AoA estimation accuracy approaching that of the single-path benchmark.

Problem

• multi-path sensing
• movable antenna
• sensing latency
• control overhead
• agile sensing

Innovation

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