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Active RIS-Enhanced UAVs network: Multi-objective optimization for joint communication and sensing
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DOI：10.1016/j.phycom.2025.102889.png)
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This paper investigates a UAV-assisted integrated sensing and communication (ISAC) system enhanced by a mobile active Reconfigurable Intelligent Surface (RIS) for multi-objective optimization. To address emergency scenarios such as urban base station failures, a cooperative network model is established, consisting of multiple UAVs and a mobile active RIS. The system simultaneously serves downlink multi-user communication and performs real-time sensing via frequency division multiple access (FDMA). A multi-objective optimization framework is formulated to jointly optimize UAVs' trajectories and transmission power, the RIS's position, phase shifts, and element-wise amplification coefficients. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) based evolutionary algorithm is proposed to balance the conflicting goals of communication throughput and sensing accuracy. Simulation results verify that the introduction of RIS, especially active RIS, significantly enhances the sensing range and communication robustness compared with the cases of no RIS and passive RIS. Further analysis reveals the trade-off between communication and sensing (C&S) performance, and evaluates the impacts of RIS element numbers, deployment strategies (mobile vs. fixed), power budgets, UAV numbers, and user densities. The results demonstrate that the dynamically optimized mobile active RIS effectively breaks through the performance bottleneck of traditional ISAC systems, providing valuable guidelines for sixth-generation (6G) UAV-enabled ISAC network design.
Keyword:
Integrated sensing and communication
Active RIS
UAV networks
Multi-objective optimization
NSGA-II
期刊
IF:
2.2
论文数:
363
被引数:
2.6K
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