Two-Stage Distributionally Robust Optimization Framework for Secure Communications in Aerial-RIS Systems

• URL: http://arxiv.org/abs/2511.22855v1
• Date: Fri, 28 Nov 2025 03:20:19 GMT
• Title: Two-Stage Distributionally Robust Optimization Framework for Secure Communications in Aerial-RIS Systems
• Authors: Zhongming Feng, Qiling Gao, Zeping Sui, Yun Lin, Michail Matthaiou,
• Abstract summary: This letter proposes a two-stage distributionally robust optimization (DRO) framework for secure deployment and beamforming in an aerial reconfigurable intelligent surface (A-RIS) assisted millimeter-wave system.<n>By employing the conditional value-at-risk (CVaR) as a distribution-free risk metric, a low-complexity algorithm is developed.<n> Simulation results validate that the proposed DRO-CVaR framework significantly enhances the tail-end secrecy spectral efficiency and maintains a lower outage probability compared to benchmark schemes.
• Score: 26.195112435634318
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This letter proposes a two-stage distributionally robust optimization (DRO) framework for secure deployment and beamforming in an aerial reconfigurable intelligent surface (A-RIS) assisted millimeter-wave system. To account for multi-timescale uncertainties arising from user mobility, imperfect channel state information (CSI), and hardware impairments, our approach decouples the long-term unmanned aerial vehicle (UAV) placement from the per-slot beamforming design. By employing the conditional value-at-risk (CVaR) as a distribution-free risk metric, a low-complexity algorithm is developed, which combines a surrogate model for efficient deployment with an alternating optimization (AO) scheme for robust real-time beamforming. Simulation results validate that the proposed DRO-CVaR framework significantly enhances the tail-end secrecy spectral efficiency and maintains a lower outage probability compared to benchmark schemes, especially under severe uncertainty conditions.

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