5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings

Research Article

A Novel Algorithm of UAV-Mounted Base Station Placement and Frequency Allocation

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  • @INPROCEEDINGS{10.1007/978-3-319-72823-0_18,
        author={Xu Shen and Zhiqing Wei and Zhiyong Feng},
        title={A Novel Algorithm of UAV-Mounted Base Station Placement and Frequency Allocation},
        proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings},
        proceedings_a={5GWN},
        year={2018},
        month={1},
        keywords={Unmanned Aerial Vehicles Mobile base station placement User coverage Soft Frequency Reuse Spectrum allocation},
        doi={10.1007/978-3-319-72823-0_18}
    }
    
  • Xu Shen
    Zhiqing Wei
    Zhiyong Feng
    Year: 2018
    A Novel Algorithm of UAV-Mounted Base Station Placement and Frequency Allocation
    5GWN
    Springer
    DOI: 10.1007/978-3-319-72823-0_18
Xu Shen1,*, Zhiqing Wei1, Zhiyong Feng1
  • 1: Beijing University of Posts and Telecommunications
*Contact email: xushen@bupt.edu.cn

Abstract

UAV equipped with base stations have recently gained significant development in cases of the terrestrial base station may not satisfy the communication command. Due to the agility and flexibility of UAV, it is used widely in disaster resilience, scenarios of unexpected and temporary events. Although UAV-mounted base station provides a fast coverage for the terrestrial users, the placement of UAVs is a problem to solve, especially the area to be covered is large which need multi-UAVs to cooperate to provide coverage. The difference of terrestrial and air-to-ground channel makes it a new coverage problem. Besides, the interference from UAVs requires a technique to manage the spectrum. In this paper, we formulate the placement of UAV as a 3-D problem, and then proposed a soft frequency reuse scheme to dynamically manage frequency resource. Simulations results show the algorithm is feasible to operate on resource-limited UAV platforms.