Qin, Yujie, 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
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 |
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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: | 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 |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/18623 |
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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