Energy Minimization for UAV-Aided Data Collection Along a Fixed Flight Path with a Directional Antenna

This paper investigates energy-minimal data collection from multiple low-power ground devices (GDs) adopting a rotary-wing unmanned aerial vehicle (UAV). Unlike most prior works that assume flexible trajectories, the UAV in our study adheres to a fixed or predetermined flight path, due to practical...

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Vydané v:IEEE transactions on communications s. 1
Hlavní autori: Zhang, Jing, Lu, Guangping, Xiang, Lin, Ge, Xiaohu, Ng, Derrick Wing Kwan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: IEEE 2025
Predmet:
Autonomous aerial vehicles
Data collection
Directional antennas
Energy consumption
Optimization
Resource management
Rotors
System performance
Trajectory
Transmitting antennas
ISSN:0090-6778, 1558-0857
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Shrnutí:This paper investigates energy-minimal data collection from multiple low-power ground devices (GDs) adopting a rotary-wing unmanned aerial vehicle (UAV). Unlike most prior works that assume flexible trajectories, the UAV in our study adheres to a fixed or predetermined flight path, due to practical requirements from e.g. patrol and inspection missions. To improve communication performance and prolong GDs' operational lifetime, the UAV employs a directional antenna for wirelessly transferring energy to the GDs before collecting their data. We jointly optimize the UAV's flight speeds, hovering locations, and radio resource allocation along the predefined flight path to minimize the UAV's total energy consumption. For acyclic flight paths, we show that the UAV's propulsion energy consumption is a strictly convex function of flight speed. However, the fixed path imposes a stringent nonconvex constraint, complicating the optimization. To overcome this challenge, we decompose the problem into two layers and solve it by proposing a novel monotonic optimization method in polar coordinates, referred to as polar polyblock approximation . This method guarantees a globally optimal solution under mild conditions. Additionally, we propose a low-complexity suboptimal algorithm to balance system performance and computational efficiency. Simulation results show that both the proposed optimal and suboptimal algorithms can effectively mitigate the limitation of a fixed flight path, resulting in significant reductions in the UAV's energy consumption during data collection, with more energy savings achieved as antenna directivity increases.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2025.3624172