Lahmeri, Mohamed-Amine, Kishk, Mustafa A. and Alouini, Mohamed-Slim (2020) Stochastic Geometry-Based Analysis of Airborne Base Stations With Laser-Powered UAVs. IEEE Communications Letters, 24 (1). pp. 173-177. ISSN 1089-7798
Preview
MK_Stochastic.pdf
Download (737kB) | Preview
Abstract
One of the most promising solutions to the problem of limited flight time of unmanned aerial vehicles (UAVs), is providing the UAVs with power through laser beams emitted from Laser Beam Directors (LBDs) deployed on the ground. In this letter, we study the performance of a laser-powered UAV-enabled communication system using tools from stochastic geometry. We first derive the energy coverage probability, which is defined as the probability of the UAV receiving enough energy to ensure successful operation (hovering and communication). Our results show that to ensure energy coverage, the distance between the UAV and its dedicated LBD must be below a certain threshold, for which we derive an expression as a function of the system parameters. Considering simultaneous information and power transmission through the laser beam using power splitting technique, we also derive the joint energy and the Signal-to-noise Ratio (SNR) coverage probability. The analytical and simulation results reveal some interesting insights. For instance, our results show that we need at least 6 LBDs/10km 2 to ensure a reliable performance in terms of energy coverage probability.
Item Type: | Article |
---|---|
Keywords: | Laser-powered UAV; simultaneous wireless information; power transmission; energy coverage; stochastic geometry; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 16995 |
Identification Number: | 10.1109/LCOMM.2019.2947039 |
Depositing User: | Mustafa Kishk |
Date Deposited: | 06 Mar 2023 15:05 |
Journal or Publication Title: | IEEE Communications Letters |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/16995 |
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 |
Repository Staff Only (login required)
Downloads
Downloads per month over past year