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 (16.05.2022-20.05.2022)
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: | 16.05.2022-20.05.2022 |
| 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, emergenCITY, Open6GHub |
| Zusätzliche Informationen: | BMBF Open6GHub |
| 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 LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY |
| Hinterlegungsdatum: | 21 Dez 2022 11:58 |
| Letzte Änderung: | 03 Apr 2024 13:07 |
| PPN: | 507301161 |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum