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Environment-Aware Deployment of Wireless Drones Base Stations with Google Earth Simulator

  • Aaron French
  • , Mohammad Mozaffari
  • , Abdelrahman Eldosouky
  • , Walid Saad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Citations (Scopus)

Abstract

In this paper, a software-based simulator for the deployment of base station-equipped unmanned aerial vehicles (UAVs) in a cellular network is proposed. To this end, the Google Earth Engine platform and its included image processing functions are used to collect geospatial data and to identify obstacles that can disrupt the line-of-sight (LoS) communications between UAVs and ground users. Given such geographical information, three environment-aware optimal UAV deployment scenarios are investigated using the developed simulator. In the first scenario, the positions of UAVs are optimized such that the number of ground users covered by UAVs is maximized. In the second scenario, the minimum number of UAVs needed to provide full coverage for all ground users is determined. Finally, given the load requirements of the ground users, the total flight time (i.e., energy) that the UAVs need to completely serve the ground users is minimized. Simulation results using a real area of the Virginia Tech campus show that the proposed environment-aware drone deployment framework with Google Earth input significantly enhances the network performance in terms of coverage and energy consumption, compared to classical deployment approaches that do not exploit geographical information. In particular, the results show that the proposed approach yields a coverage enhancement by a factor of 2, and a 65% improvement in energy-efficiency. The results have also shown the existence of an optimal number of drones that leads to a maximum wireless coverage performance.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages868-873
Number of pages6
ISBN (Electronic)9781538691519
DOIs
Publication statusPublished - Mar 2019
Event2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 - Kyoto, Japan
Duration: 11 Mar 201915 Mar 2019

Publication series

Name2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019

Conference

Conference2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
Country/TerritoryJapan
CityKyoto
Period11/03/1915/03/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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