Movable Antenna-Enabled Integrated Sensing and Communication in Low-Altitude UAV Networks
Bin Li, Pengcheng Rao, Xuedong Zhang, Xinyi Wang

TL;DR
This paper proposes a movable antenna-enabled UAV system for integrated sensing and communication, optimizing trajectories, antenna positions, and beamforming to improve data rates and sensing performance in dynamic scenarios.
Contribution
It introduces a joint optimization framework using clustering and reinforcement learning for movable antenna UAV-assisted ISAC systems, addressing practical mobility challenges.
Findings
Movable antennas outperform fixed antennas in ISAC UAV systems.
The proposed optimization improves data rates and sensing performance.
Clustering-based flight direction suggestions enhance UAV deployment.
Abstract
This paper investigates a multiple unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) system equipped with movable antenna (MA) arrays. To align with practical scenarios, we simulate the dynamic roaming of ground users and the three-dimensional deployment of UAVs in the airspace. We aim to maximize the total data rate by jointly optimizing key operational variables, including UAV trajectories, user association, antenna positions, and beamforming. This formulated problem is subject to constraints on transmission power and the sensing signal-to-noise ratio. To address the challenge of dynamically unknown state transitions due to user mobility, the original problem is decomposed into two steps and solved using different algorithms. First, we utilize the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm to address…
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