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    Stochastic Geometry-Based Trajectory Design for Multi-Purpose UAVs: Package and Data Delivery


    Qin, Yujie and Kishk, Mustafa A. and Alouini, Mohamed-Slim (2024) Stochastic Geometry-Based Trajectory Design for Multi-Purpose UAVs: Package and Data Delivery. IEEE Transactions on Vehicular Technology, 73 (3). pp. 4136-4150. ISSN 0018-9545

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    Official URL: https://doi.org/10.1109/TVT.2023.3323682


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    Abstract

    With the advancements achieved in drones’ flexibility, low cost, and high efficiency, they obtain huge application opportunities in various industries, such as aerial delivery and future communication networks. However, the increasing transportation needs and expansion of network capacity demands for UAVs will cause aerial traffic conflicts in the future. To address this issue, in this article, we explore the idea of multi-purpose UAVs, which act as aerial wireless communication data relays and means of aerial transportation simultaneously to deliver data and packages at the same time. While UAVs deliver the packages from warehouses to residential areas, we design their trajectories which enable them to collect data from multiple Internet of Things (IoT) clusters and forward the collected data to terrestrial base stations (TBSs). To select the serving nearby IoT clusters, UAVs rank them based on their priorities and distances. From the perspectives of data and package delivery, respectively, we propose two algorithms that design the optimal UAVs trajectory to maximize the transmitted data or minimize the round trip time. Specifically, we use tools from stochastic geometry to model the locations of IoT clusters and TBSs. Given the nature of random locations, the proposed algorithm applies to general cases. Our numerical results show that multi-purpose UAVs are practical and have great potential to enhance the energy/time-efficiency of future networks.

    Item Type: Article
    Keywords: Stochastic geometry; multi-purpose UAVs; package delivery; data collection; Internet of Things (IoT) devices; poisson point process; trajectory planning;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 18623
    Identification Number: https://doi.org/10.1109/TVT.2023.3323682
    Depositing User: Mustafa Kishk
    Date Deposited: 07 Jun 2024 14:24
    Journal or Publication Title: IEEE Transactions on Vehicular Technology
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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