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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.22855 |
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| _version_ | 1866911291981955072 |
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| author | Feng, Zhongming Gao, Qiling Sui, Zeping Lin, Yun Matthaiou, Michail |
| author_facet | Feng, Zhongming Gao, Qiling Sui, Zeping Lin, Yun Matthaiou, Michail |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_22855 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Two-Stage Distributionally Robust Optimization Framework for Secure Communications in Aerial-RIS Systems Feng, Zhongming Gao, Qiling Sui, Zeping Lin, Yun Matthaiou, Michail Information Retrieval Information Theory 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. |
| title | Two-Stage Distributionally Robust Optimization Framework for Secure Communications in Aerial-RIS Systems |
| topic | Information Retrieval Information Theory |
| url | https://arxiv.org/abs/2511.22855 |