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

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

doi:10.1109/SPAWC.2018.8445906

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

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

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538635124
DOIs	https://doi.org/10.1109/SPAWC.2018.8445906
Publication status	Published - 2018 Aug 24
Event	19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 - Kalamata, Greece Duration: 2018 Jun 25 → 2018 Jun 28

Publication series

Name	IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume	2018-June

Other

Other	19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Country	Greece
City	Kalamata
Period	18/6/25 → 18/6/28

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

Access to Document

10.1109/SPAWC.2018.8445906

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Cite this

Kim, H., Park, J., Bennis, M., & Kim, S. L. (2018). Massive UAV-to-Ground Communication and its Stable Movement Control: A Mean-Field Approach. In 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 [8445906] (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2018.8445906

Kim, Hyesung ; Park, Jihong ; Bennis, Mehdi ; Kim, Seong Lyun. / Massive UAV-to-Ground Communication and its Stable Movement Control : A Mean-Field Approach. 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC).

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

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.",

author = "Hyesung Kim and Jihong Park and Mehdi Bennis and Kim, {Seong Lyun}",

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.; 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 ; Conference date: 25-06-2018 Through 28-06-2018",

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Kim, H, Park, J, Bennis, M & Kim, SL 2018, Massive UAV-to-Ground Communication and its Stable Movement Control: A Mean-Field Approach. in 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018., 8445906, IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018, Kalamata, Greece, 18/6/25. https://doi.org/10.1109/SPAWC.2018.8445906

Massive UAV-to-Ground Communication and its Stable Movement Control : A Mean-Field Approach. / Kim, Hyesung; Park, Jihong; Bennis, Mehdi; Kim, Seong Lyun.

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8445906 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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Kim H, Park J, Bennis M, Kim SL. Massive UAV-to-Ground Communication and its Stable Movement Control: A Mean-Field Approach. In 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8445906. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC). https://doi.org/10.1109/SPAWC.2018.8445906