Low-Complexity Algorithm for Outage Optimal Resource Allocation in Energy Harvesting-Based UAV Identification Networks

We study an unmanned aerial vehicle (UAV) identification network equipped with an energy harvesting (EH) technique. In the network, the UAVs harvest energy through radio frequency (RF) signals transmitted from ground control stations (GCSs) and then transmit their identification information to the g...

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Veröffentlicht in:IEEE communications letters Jg. 25; H. 11; S. 3639 - 3643
Hauptverfasser: Park, Jae Cheol, Kang, Kyu-Min, Choi, Junil
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Bandwidth
Bandwidths
Closed form solutions
Energy harvesting
Exact solutions
Ground stations
Mathematical analysis
Optimization
outage probability
Outages
Performance evaluation
Power system reliability
Probability
Radio frequency
Radio signals
Regulation
Resource allocation
Resource management
Signal to noise ratio
UAV identification
unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
ISSN:1089-7798, 1558-2558
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Zusammenfassung:We study an unmanned aerial vehicle (UAV) identification network equipped with an energy harvesting (EH) technique. In the network, the UAVs harvest energy through radio frequency (RF) signals transmitted from ground control stations (GCSs) and then transmit their identification information to the ground receiver station (GRS). Specifically, we first derive a closed-form expression of the outage probability to evaluate the network performance. Then we obtain the closed-form expression of the optimal time allocation when the bandwidth is equally allocated to the UAVs. We also propose a fast-converging algorithm for time and the bandwidth allocation, which is necessary for the UAV environment with high mobility, to optimize the outage performance of EH-based UAV identification network. Simulation results show that the proposed algorithm outperforms the conventional bisection algorithm and achieves near-optimal performance.
Bibliographie:ObjectType-Article-1
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2021.3106512