A predictive on-demand placement of UAV base stations using echo state network

Haoran Peng, Chao Chen, Chuan Chi Lai, Li Chun Wang, Zhu Han

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

2 Scopus citations

Abstract

The unmanned aerial vehicles base stations (UAV-BSs) have great potential in being widely used in many dynamic application scenarios. In those scenarios, the movements of served user equipments (UEs) are inevitable, so the UAV-BSs needs to be re-positioned dynamically for providing seamless services. In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories. An Echo State Network (ESN) based algorithm for predicting the future trajectories of UEs and a Kuhn-Munkres-based algorithm for finding the energy-efficient reposition trajectories of UAV-BSs is designed, respectively. We conduct a simulation using a real open dataset for performance validation. The simulation results indicate that the proposed framework achieves high prediction accuracy and provides the energy-efficient matching scheme.

Original languageEnglish
Title of host publication2019 IEEE/CIC International Conference on Communications in China, ICCC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages36-41
Number of pages6
ISBN (Electronic)9781728107325
DOIs
StatePublished - Aug 2019
Event2019 IEEE/CIC International Conference on Communications in China, ICCC 2019 - Changchun, China
Duration: 11 Aug 201913 Aug 2019

Publication series

Name2019 IEEE/CIC International Conference on Communications in China, ICCC 2019

Conference

Conference2019 IEEE/CIC International Conference on Communications in China, ICCC 2019
CountryChina
CityChangchun
Period11/08/1913/08/19

Keywords

  • Base Station
  • Echo State Network
  • Kuhn-Munkres Algorithm
  • Prediction
  • Unmanned Aerial Vehicle

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