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Energy-Efficient and Secure Communications for UAV-RIS-Assisted Multi-User Multi-Eavesdropper Networks via Joint UAV Deployment, RIS Partitioning, Beamforming, and Phase Shift Design
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DOI：10.1109/tgcn.2026.3717661.png)
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Abstract
En 中文
The integration of reconfigurable intelligent surface (RIS) and uncrewed aerial vehicle (UAV) can extend wireless coverage and improve link reliability. However, the broadcast nature of wireless channels exposes the UAV-RIS system to severe information leakage risks in multi-eavesdropper environments, while the high energy consumption of the system poses an additional challenge to green communications. To balance secure transmission and green communication, this paper proposes a UAV-RIS-assisted multi-user multi-eavesdropper secure communication network and designs a virtual RIS partitioning mechanism. Specifically, the RIS is partitioned into multiple virtual sub-segments, and by configuring the phase shifts of each sub-segment to align with the cascaded channel of a specific legitimate user or eavesdropper, signal enhancement and directional artificial noise (AN) jamming can be simultaneously achieved. On this basis, a system power consumption model is established, and joint optimization of UAV three-dimensional (3D) deployment, RIS partitioning, base station (BS) transmit precoding, AN covariance matrix, and RIS phase shifts is performed to maximize the secrecy energy efficiency (SEE). This problem is a mixed-integer non-convex fractional optimization problem. To solve it efficiently, this paper develops a double-layer iterative algorithm that combines the Dinkelbach transform and alternating optimization (AO). UAV deployment is solved via successive convex approximation (SCA), RIS partitioning is optimized using a discretized Capuchin search algorithm (CapSA), and semidefinite relaxation (SDR) is applied to the beamforming and phase shift subproblems. Numerical results demonstrate that the proposed scheme achieves significant advantages in improving the system SEE.
Keywords:
Reconfigurable intelligent surface
uncrewed aerial vehicle
artificial noise
alternating optimization
secrecy energy efficiency
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