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A Global Optimization Method for Energy-Minimal UAV-Aided Data Collection over Fixed Flight Path

Lu, Guangping ; Zhang, Jing ; Xiang, Lin ; Ge, Xiaohu (2022)
A Global Optimization Method for Energy-Minimal UAV-Aided Data Collection over Fixed Flight Path.
2022 IEEE International Conference on Communications. Seoul, Republic of Korea (16.-20.05.2022)
doi: 10.1109/ICC45855.2022.9838554
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

This paper considers optimal resource allocation for data collection from multiple ground devices (GDs) using a rotary-wing unmanned aerial vehicle (UAV). The UAV’s flight path, i.e., the sequence of moving positions, is given a priori due to requirements of e.g. patrol and inspection missions, whereas the UAV’s trajectory, i.e., the path and time schedule of movement, remains dependent on its hovering positions and flying speeds along the path. To improve the spectral and energy efficiency of the GDs, the UAV employs a directional antenna and performs wireless power transfer (WPT) to the GDs before collecting data from them. We jointly optimize the UAV’s flying speeds, hovering locations, and radio resource allocation (including time, bandwidth and transmit power) for minimization of the total energy consumption of the UAV required for completing data collection along the flying path. We show that given any flight path, the propulsion energy consumption of the UAV is a convex function of the flight speeds. However, due to the highly directive transmission, communication and flight of the UAV become strongly coupled and complicates the problem, e.g. the selection of the UAV’s hovering points will affect both the order of serving the GDs and the antenna gain of the UAV. Moreover, nonconvexity in the flight path constraints further obscures an efficient solution to the resource allocation problem. To tackle these challenges, we propose an iterative algorithm based on the branch-and-bound (BnB) method, which can obtain the globally optimal solution when the flight path coincides with the boundary of a convex set. Simulation results show that compared with several baseline algorithms, the proposed algorithm can significantly lower the energy consumption of the UAV during data collection.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Lu, Guangping ; Zhang, Jing ; Xiang, Lin ; Ge, Xiaohu
Art des Eintrags: Bibliographie
Titel: A Global Optimization Method for Energy-Minimal UAV-Aided Data Collection over Fixed Flight Path
Sprache: Englisch
Publikationsjahr: 11 August 2022
Verlag: IEEE
Buchtitel: ICC 2022 - IEEE International Conference on Communications
Veranstaltungstitel: 2022 IEEE International Conference on Communications
Veranstaltungsort: Seoul, Republic of Korea
Veranstaltungsdatum: 16.-20.05.2022
DOI: 10.1109/ICC45855.2022.9838554
URL / URN: https://ieeexplore.ieee.org/document/9838554
Kurzbeschreibung (Abstract):

This paper considers optimal resource allocation for data collection from multiple ground devices (GDs) using a rotary-wing unmanned aerial vehicle (UAV). The UAV’s flight path, i.e., the sequence of moving positions, is given a priori due to requirements of e.g. patrol and inspection missions, whereas the UAV’s trajectory, i.e., the path and time schedule of movement, remains dependent on its hovering positions and flying speeds along the path. To improve the spectral and energy efficiency of the GDs, the UAV employs a directional antenna and performs wireless power transfer (WPT) to the GDs before collecting data from them. We jointly optimize the UAV’s flying speeds, hovering locations, and radio resource allocation (including time, bandwidth and transmit power) for minimization of the total energy consumption of the UAV required for completing data collection along the flying path. We show that given any flight path, the propulsion energy consumption of the UAV is a convex function of the flight speeds. However, due to the highly directive transmission, communication and flight of the UAV become strongly coupled and complicates the problem, e.g. the selection of the UAV’s hovering points will affect both the order of serving the GDs and the antenna gain of the UAV. Moreover, nonconvexity in the flight path constraints further obscures an efficient solution to the resource allocation problem. To tackle these challenges, we propose an iterative algorithm based on the branch-and-bound (BnB) method, which can obtain the globally optimal solution when the flight path coincides with the boundary of a convex set. Simulation results show that compared with several baseline algorithms, the proposed algorithm can significantly lower the energy consumption of the UAV during data collection.

Freie Schlagworte: emergenCITY_KOM
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Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Kommunikationstechnik
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Hinterlegungsdatum: 21 Dez 2022 11:58
Letzte Änderung: 27 Apr 2023 06:20
PPN: 507301161
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