Rate Maximization for UAV-assisted ISAC System with Fluid Antennas

This letter investigates the joint sensing problem between unmanned aerial vehicles (UAV) and base stations (BS) in integrated sensing and communication (ISAC) systems with fluid antennas (FA). In this system, the BS enhances its sensing performance through the UAV’s perception system. We aim to maximize the communication rate between the BS and UAV while guaranteeing the joint system’s sensing capability. By establishing a communication-sensing model with convex optimization properties, we decompose the problem and apply convex optimization to progressively solve key variables. An iterative algorithm employing an alternating optimization approach is subsequently developed to determine the optimal solution, significantly reducing the solution complexity. Simulation results validate the algorithm’s effectiveness in balancing system performance.

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Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/icccworkshops67136.2025.11148178
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
4.99
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article

Rate Maximization for UAV-assisted ISAC System with Fluid Antennas

Zhengya Guo, Zhaohui Yang, Xiaogan Yang, Zhaoyang Zhang et al.
1 citations
UAV Applications and Optimization
4.99
article

Rate Maximization for UAV-assisted ISAC System with Fluid Antennas

Zhengya Guo, Zhaohui Yang, Xiaogan Yang, Zhaoyang Zhang, Siyun Liang, Chen Ying Zhu
article en
1 citations

Abstract

This letter investigates the joint sensing problem between unmanned aerial vehicles (UAV) and base stations (BS) in integrated sensing and communication (ISAC) systems with fluid antennas (FA). In this system, the BS enhances its sensing performance through the UAV’s perception system. We aim to maximize the communication rate between the BS and UAV while guaranteeing the joint system’s sensing capability. By establishing a communication-sensing model with convex optimization properties, we decompose the problem and apply convex optimization to progressively solve key variables. An iterative algorithm employing an alternating optimization approach is subsequently developed to determine the optimal solution, significantly reducing the solution complexity. Simulation results validate the algorithm’s effectiveness in balancing system performance.

Zhejiang University of Science and Technology (CN), Hangzhou Wanxiang Polytechnic (CN), Zhejiang University (CN)
Openalex Percentile: Top 5%
UAV Applications and Optimization
4.99
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