Massive UAV-to-Ground Communication and its Stable Movement Control: A Mean-Field Approach

Hyesung Kim, Jihong Park, Mehdi Bennis, Seong Lyun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

This paper proposes a real-time movement control algorithm for massive unmanned aerial vehicles (UAV s) that provide emergency cellular connections in an urban disaster site. While avoiding the inter-Uavcollision under temporal wind dynamics, the proposed algorithm minimizes each UAV's energy consumption per unit downlink rate. By means of a mean-field game theoretic flocking approach, the velocity control of each UAV only requires its own location and channel states. Numerical results validate the performance of the algorithm in terms of the number of collisions and energy consumption per data rate, under a realistic 3GPP UAV channel model.

Original languageEnglish
Title of host publication2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538635124
DOIs
Publication statusPublished - 2018 Aug 24
Event19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 - Kalamata, Greece
Duration: 2018 Jun 252018 Jun 28

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2018-June

Other

Other19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
CountryGreece
CityKalamata
Period18/6/2518/6/28

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT This research was supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(NRF-2017R1A2A2A05069810), in part by the Academy of Finland project CARMA, in part by the INFOTECH project NOOR, and in part by the Kvantum Institute strategic project SAFARI.

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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