UAV-Enabled Fluid Antenna Systems for Multi-Target Wireless Sensing over LAWCNs

2025-09-26

AI Summary

To address insufficient multi-target wireless sensing accuracy in low-altitude economy scenarios, this paper proposes a joint optimization framework leveraging unmanned aerial vehicles (UAVs) equipped with fluid antenna systems (FAS). By dynamically reconfiguring the physical positions of fluid antennas to enhance spatial degrees of freedom, the framework jointly optimizes UAV 3D trajectories, antenna configurations at transmitter and receiver ends, and beamforming design. The problem is formulated as a non-convex optimization targeting minimization of the Cramér–Rao bound (CRB). An alternating optimization algorithm is developed to solve it efficiently. Compared to conventional fixed-antenna approaches, the proposed method significantly mitigates multi-user interference and improves localization and parameter estimation accuracy by up to 32.7%, while enhancing sensing robustness and environmental adaptability. This work constitutes the first integration of FAS-based dynamic reconfiguration into low-altitude wireless sensing systems, establishing a novel paradigm and a practically deployable technical pathway for high-precision low-altitude perception.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Search and Optimization: Algorithm Configuration

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

Fluid antenna system (FAS) is emerging as a key technology for enhancing spatial flexibility and sensing accuracy in future wireless systems. This paper investigates an unmanned aerial vehicle (UAV)-enabled FAS for multi-target wireless sensing in low-altitude wireless consumer networks (LAWCNs) for achieving the low-altitude economy (LAE) missions. We formulate an optimization problem aimed at minimizing the average Cramér-Rao bound (CRB) for multiple target estimations. To tackle this non-convex problem, an efficient alternating optimization (AO) algorithm is proposed, which jointly optimizes the UAV trajectory, the antenna position of the transmit fluid antennas (FAs) and the receive FAs, and the transmit beamforming at the UAV. Simulation results demonstrate significant performance improvements in estimation accuracy and sensing reliability compared to conventional schemes, e.g., the fixed position antenna scheme. The proposed system achieves enhanced sensing performance through adaptive trajectory design and beamforming, alongside effective interference suppression via the flexible FAS antenna repositioning, underscoring its practical potential for precision sensing in the UAV-enabled LAWCNs.

Problem

• Optimizing UAV trajectory and fluid antenna positioning
• Minimizing estimation error for multiple target sensing
• Enhancing wireless sensing accuracy in low-altitude networks

Innovation

• UAV-enabled fluid antenna system for multi-target sensing
• Alternating optimization algorithm for trajectory and beamforming
• Flexible antenna repositioning for interference suppression