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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/2504.20425 |
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| _version_ | 1866918004060585984 |
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| author | Van Chien, Trinh Quan, Nguyen Minh Shin, Oh-Soon Nguyen, Van-Dinh |
| author_facet | Van Chien, Trinh Quan, Nguyen Minh Shin, Oh-Soon Nguyen, Van-Dinh |
| contents | The integration of unmanned aerial vehicles (UAVs) into wireless communication systems has emerged as a transformative approach, promising cost-efficient connectivity. This paper addresses the optimization of the dynamic time-splitting ratio and flight trajectory for a communication system linking a ground base station to the UAV equipped with backscatter devices (referred to as UB), and from UB to an end user. Given the inherent non-convexity of the problem, we develop two meta-heuristic-based approaches inspired by genetic algorithm and particle swarm optimization to enhance the total achievable rate while reducing computational complexity. Numerical results demonstrate the effectiveness of these meta-heuristic solutions, showcasing significant improvements in the achievable rate and computation time compared to existing benchmarks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_20425 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Metaheuristic Optimization of Trajectory and Dynamic Time Splitting for UAV Communication Systems Van Chien, Trinh Quan, Nguyen Minh Shin, Oh-Soon Nguyen, Van-Dinh Information Theory The integration of unmanned aerial vehicles (UAVs) into wireless communication systems has emerged as a transformative approach, promising cost-efficient connectivity. This paper addresses the optimization of the dynamic time-splitting ratio and flight trajectory for a communication system linking a ground base station to the UAV equipped with backscatter devices (referred to as UB), and from UB to an end user. Given the inherent non-convexity of the problem, we develop two meta-heuristic-based approaches inspired by genetic algorithm and particle swarm optimization to enhance the total achievable rate while reducing computational complexity. Numerical results demonstrate the effectiveness of these meta-heuristic solutions, showcasing significant improvements in the achievable rate and computation time compared to existing benchmarks. |
| title | Metaheuristic Optimization of Trajectory and Dynamic Time Splitting for UAV Communication Systems |
| topic | Information Theory |
| url | https://arxiv.org/abs/2504.20425 |