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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2509.23908 |
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| _version_ | 1866909813082947584 |
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| author | Wang, Qingyang Yao, Zhuohui Cheng, Wenchi Zheng, Xiao |
| author_facet | Wang, Qingyang Yao, Zhuohui Cheng, Wenchi Zheng, Xiao |
| contents | This paper proposes a rate-splitting multiple access (RSMA) transmission scheme to maximize the minimum achievable rate among ground users for emergency communications in post-disaster scenarios with obstacles, with which the optimal positioning of multiple unmanned aerial vehicle (UAV)-enabled base stations can be achieved timely.To address the resulting non-convex and intractable optimization problem, we design an alternating optimization approach. Specifically, we relax obstacle-related constraints using penalty terms. In each iteration, block coordinate descent (BCD) and successive convex approximation (SCA) are applied alternately to obtain locally optimal solutions, and penalty multipliers are updated to ensure convergence of the relaxed problem to the original one. Simulation results demonstrate that the proposed scheme significantly outperforms benchmark methods in terms of the minimum achievable rate, verifying its effectiveness and superiority. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_23908 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Post-disaster Max-Min Rate Optimization for Multi-UAV RSMA Network in Obstacle Environments Wang, Qingyang Yao, Zhuohui Cheng, Wenchi Zheng, Xiao Information Theory This paper proposes a rate-splitting multiple access (RSMA) transmission scheme to maximize the minimum achievable rate among ground users for emergency communications in post-disaster scenarios with obstacles, with which the optimal positioning of multiple unmanned aerial vehicle (UAV)-enabled base stations can be achieved timely.To address the resulting non-convex and intractable optimization problem, we design an alternating optimization approach. Specifically, we relax obstacle-related constraints using penalty terms. In each iteration, block coordinate descent (BCD) and successive convex approximation (SCA) are applied alternately to obtain locally optimal solutions, and penalty multipliers are updated to ensure convergence of the relaxed problem to the original one. Simulation results demonstrate that the proposed scheme significantly outperforms benchmark methods in terms of the minimum achievable rate, verifying its effectiveness and superiority. |
| title | Post-disaster Max-Min Rate Optimization for Multi-UAV RSMA Network in Obstacle Environments |
| topic | Information Theory |
| url | https://arxiv.org/abs/2509.23908 |