Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief

Long D. Nguyen; Khoi K. Nguyen; Ayse Kortun; Trung Q.  Duong

doi:10.1109/SPAWC.2019.8815522

Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief

Long D. Nguyen, Khoi K. Nguyen, Ayse Kortun, Trung Q. Duong

School of Electronics, Electrical Engineering and Computer Science

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

45 Citations (Scopus)

Abstract

In this work, we propose a robust and efficient resource allocation scheme for UAV-enabled cellular networks that aid in disaster communications. To recover the network within a disaster area, a fast user clustering model based on K-means procedure and distributed control power coefficient will be proposed and can be embedded in the real system by using UAV-assisted relaying for real-time recovering and maintaining network during and after disasters. Algorithms of low computational complexity and fast convergence are also proposed. Numerical examples are provided to demonstrate the benefit of the proposed computational approach.

Original language	English
Title of host publication	IEEE SPAWC
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	978-1-5386-6529-9
DOIs	https://doi.org/10.1109/SPAWC.2019.8815522
Publication status	Published - 29 Aug 2019

Publication series

Name	2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Publisher	IEEE
ISSN (Electronic)	1948-3252

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10.1109/SPAWC.2019.8815522Licence: Unspecified

Reconfigurable intelligent surface and UAV-assisted communications: A deep reinforcement learning approach
Nguyen, K. K. (Author), Duong, Q. (Supervisor), Jul 2022
Student thesis: Doctoral Thesis › Doctor of Philosophy

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Nguyen, L. D., Nguyen, K. K., Kortun, A., & Duong, T. Q. (2019). Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief. In IEEE SPAWC (2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2019.8815522

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title = "Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief",

abstract = "In this work, we propose a robust and efficient resource allocation scheme for UAV-enabled cellular networks that aid in disaster communications. To recover the network within a disaster area, a fast user clustering model based on K-means procedure and distributed control power coefficient will be proposed and can be embedded in the real system by using UAV-assisted relaying for real-time recovering and maintaining network during and after disasters. Algorithms of low computational complexity and fast convergence are also proposed. Numerical examples are provided to demonstrate the benefit of the proposed computational approach.",

author = "Nguyen, {Long D.} and Nguyen, {Khoi K.} and Ayse Kortun and Duong, {Trung Q.}",

year = "2019",

month = aug,

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doi = "10.1109/SPAWC.2019.8815522",

language = "English",

isbn = "978-1-5386-6529-9",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief. / Nguyen, Long D.; Nguyen, Khoi K.; Kortun, Ayse et al.
IEEE SPAWC. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)).

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

TY - GEN

T1 - Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief

AU - Nguyen, Long D.

AU - Nguyen, Khoi K.

AU - Kortun, Ayse

AU - Duong, Trung Q.

PY - 2019/8/29

Y1 - 2019/8/29

N2 - In this work, we propose a robust and efficient resource allocation scheme for UAV-enabled cellular networks that aid in disaster communications. To recover the network within a disaster area, a fast user clustering model based on K-means procedure and distributed control power coefficient will be proposed and can be embedded in the real system by using UAV-assisted relaying for real-time recovering and maintaining network during and after disasters. Algorithms of low computational complexity and fast convergence are also proposed. Numerical examples are provided to demonstrate the benefit of the proposed computational approach.

AB - In this work, we propose a robust and efficient resource allocation scheme for UAV-enabled cellular networks that aid in disaster communications. To recover the network within a disaster area, a fast user clustering model based on K-means procedure and distributed control power coefficient will be proposed and can be embedded in the real system by using UAV-assisted relaying for real-time recovering and maintaining network during and after disasters. Algorithms of low computational complexity and fast convergence are also proposed. Numerical examples are provided to demonstrate the benefit of the proposed computational approach.

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DO - 10.1109/SPAWC.2019.8815522

M3 - Conference contribution

SN - 978-1-5386-6529-9

T3 - 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

BT - IEEE SPAWC

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Real-Time Deployment and Resource Allocation for Distributed UAV Systems in Disaster Relief

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Student theses

Reconfigurable intelligent surface and UAV-assisted communications: A deep reinforcement learning approach

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