Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm

Xingyu Zhu

doi:10.47297/taposatWSP2633-456945.20250608

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Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm

6卷第8期

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Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm
Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm
School of Humanities, Beijing Institute of Technology, Haidian District, Beijing, 100081, China
2025年6卷第8期页码：240-244
纸质出版：2025-08-30
DOI：10.47297/taposatWSP2633-456945.20250608
Accepted：

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(2025). Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm. 科技理论与实践（英文版）, 6(8), 240-244.

Zhu Xingyu.Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm[J].Theory and Practice of Science and Technology,2025,06(08):240-244.
(2025). Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm. 科技理论与实践（英文版）, 6(8), 240-244. DOI： 10.47297/taposatWSP2633-456945.20250608.

Zhu Xingyu.Research on Ground Wide-Area Network Communication Coverage Method Based on Multi-UAV Swarm[J].Theory and Practice of Science and Technology,2025,06(08):240-244. DOI： 10.47297/taposatWSP2633-456945.20250608.

摘要

Abstract

With the rapid development of 5G/6G

smart cities

and emergency communications

traditional ground communication infrastructure has exposed bottlenecks such as long deployment cycles and poor adaptability in rapid response

wide-area coverage

and dynamic scheduling. Due to their high mobility

flexible networking

and rapid deployment capabilities

multi-UAV swarms are regarded as a key technology to enhance ground wide-area network communication coverage. However

shortcomings remain in multi-dimensional environment perception

swarm adaptive control and self-healing

and edge intelligence collaboration and proactive resource scheduling capabilities. This paper proposes a comprehensive method integrating multi-source heterogeneous perception—edge computing—multi-agent reinforcement learning (MARL)—and user intention prediction

aiming to achieve wide-area communication coverage and resilience enhancement in complex dynamic environments. It also proposes a simulation–physical system integrated verification approach. The core ideas include: constructing a swarm self-organizing/self-healing model driven by multi-dimensional perception

designing edge intelligence collaboration and global consistency mechanisms

establishing a user-intention-driven proactive resource scheduling system

and building an evaluation framework based on NS-3/OMNeT++ and physical platforms. The proposed solution is oriented toward scenarios such as emergency communication

smart cities

and coverage in remote areas

demonstrating significant potential for engineering application.

关键词

Keywords

references

Lu Maomao, Liu Chunhui, Dong Zanliang. Dynamic Communication Resource Allocation Method for Multi-UAV Regional Coverage [J]. Journal of Beijing University of Aeronautics and Astronautics, 2024, 50(9): 2939–2950.

CN109753082B. Cooperative Communication Method for Multi-UAV Networks [Patent].

Li Hechen, Huang Zixuan, Zhang Jing, et al. Time Slot Resource Allocation in UAV Ad Hoc Networks under Limited Connectivity [EB/OL]. China Science and Technology Papers Online, 2024-06-12.

Qingqing Wu, Yong Zeng, Rui Zhang. Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks. arXiv preprint arXiv: 1705.02723 , 2017.

Yong Zeng, Jie Xu, Rui Zhang. Energy Minimization for Wireless Communication with Rotary-Wing UAV. arXiv preprint arXiv: 1804.02238 , 2018.

Tengchan Zeng, Mohammad Mozaffari, Omid Semiari, et al. Wir eless Communications and Control for Swarms of Cellular-Connected UAVs. arXiv preprint arXiv: 1812.00743 , 2018.

S. Rosati, K. Kruzelecki, G. Heitz, et al. Dynamic Routing for Flying Ad Hoc Networks. arXiv preprint arXiv: 1406.4399 , 2014.

Khan, M.A., Rehman, A., Rehman, S.U., et al. Swarm of UAVs for Network Management in 6G: A Technical Review. arXiv preprint arXiv: 2205.07286 , 2022.

Chen, X., Tang, J., Lao, S. A Review of Unmanned Aerial Vehicle Swarm Communication Architectures and Routing Protocols. Applied Sciences , 10(24), 8722, 2020.

Zeng, Y., Zhang, R. Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges. IEEE Communications Magazine , 54(5), 36-42, 2016.

Zeng, Y., Xu, J., Zhang, R. Energy Minimization for Wireless Communication with Rotary-Wing UAV. IEEE Transactions on Wireless Communications , 18(4), 2329-2345, 2019.

Wu, Q., Zeng, Y., Zhang, R. Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks. IEEE Transactions on Wireless Communications , 17(3), 2109-2121, 2018.

Mozaffari, M., Saad, W., Bennis, M., Debbah, M. Unmanned Aerial Vehicle with Underlaid Device-to-Device Communications: Performance and Tradeoffs. IEEE Transactions on Wireless Communications , 15(6), 3949-3963, 2016.

Zeng, T., Mozaffari, M., Semiari, O., Saad, W., Bennis, M., Debbah, M.Wireless Communications and Control for Swarms of Cellular-Connected UAVs. arXiv preprint arXiv: 1812.00743 , 2018.

Rosati, S., Kruzelecki, K., Heitz, G., Floreano, D., Rimoldi, B.Dynamic Routing for Flying Ad Hoc Networks. arXiv preprint arXiv: 1406.4399 , 2014.

Wang, Y., Zhang, Y., Liu, Y., Xue, Y., Xia, Y. Resilience evaluation for UAV swarm performing joint reconnaissance mission. Chaos: An Interdisciplinary Journal of Nonlinear Science , 32(1), 2022.

Alsamhi, S.H., Ma, O., Ansari, M.S., Meng, Q. Survey on Collaborative Smart Drones: Coordination, Swarming, and Decision Making. Drones , 5(1), 2021.

Sharma, V., You, I., Atiquzzaman, M. A Survey on Multi-UAV Path Planning: Classification, Algorithms, and Future Challenges. Drones , 4(4), 2020.

Zhou, S., et al. Unmanned Aerial Vehicle Swa rm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges. arXiv preprint arXiv: 2302.10074 , 2023.

Chen, S., et al. Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics. arXiv preprint arXiv: 2312.11227 , 2023.

Deng, H., Han, Z., Yu, H., Xiong, N.N. Toward Near-Space Communication Network in the 6G and Beyond. arXiv preprint arXiv: 2404.06155 , 2024.

Arafat, M.Y., Moh, S. AI-Enabled Routing Protocols for UAV Networks: Trends, Challenges, and Future Outlook. arXiv preprint arXiv: 2312.08471 , 2023.

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