Optimization of UAV-Aided Millimeter-Wave IoT Systems

Due to their maneuverability, unmanned aerial vehicles (UAVs) have grown into a promising enabler of the Internet of Things (IoTs). In addition to the benefits of the bandwidth and communication quality of millimeter-wave (mmWave) systems, a UAV-aided mmWave multiple-input and multiple-output (MIMO)...

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Autores principales:	Xingxuan Zuo, Lingfeng Shen, Gangtao Han, Xiaomin Mu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	unmanned aerial vehicle Internet of Things (IoT) millimeter-wave (mmWave) trajectory planning beamspace multiple-input multiple-output (MIMO) Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/bd530ac0d37442189ce8e6045a7adbdf
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id	oai:doaj.org-article:bd530ac0d37442189ce8e6045a7adbdf
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spelling	oai:doaj.org-article:bd530ac0d37442189ce8e6045a7adbdf2021-11-11T15:38:20ZOptimization of UAV-Aided Millimeter-Wave IoT Systems10.3390/electronics102126182079-9292https://doaj.org/article/bd530ac0d37442189ce8e6045a7adbdf2021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2618https://doaj.org/toc/2079-9292Due to their maneuverability, unmanned aerial vehicles (UAVs) have grown into a promising enabler of the Internet of Things (IoTs). In addition to the benefits of the bandwidth and communication quality of millimeter-wave (mmWave) systems, a UAV-aided mmWave multiple-input and multiple-output (MIMO) communication system is investigated in this paper for the data collection of IoT systems, in which single-antenna IoT devices are divided into several clusters, and the UAV aided mmWave base station (UAV-BS) collects data from each cluster using the time division scheme. The joint optimization of the beam selection, UAV trajectory, user clustering, power allocation and transmission duration is studied in this paper to improve the data collection efficiency. The solution of the problem is then given in three steps. Firstly, the incremental <i>K</i>-means clustering and ant colony optimization algorithm are utilized to handle the UAV trajectory planning and user clustering problem. Secondly, an incremental beam selection scheme is employed to ensure that all the devices in each cluster can communicate with the UAV. Thirdly, an iterative algorithm is proposed by alternately optimizing the power allocation and transmission duration of the IoT devices. Finally, the simulation results demonstrate the effectiveness of the proposed solution for the UAV-aided mmWave communication system.Xingxuan ZuoLingfeng ShenGangtao HanXiaomin MuMDPI AGarticleunmanned aerial vehicleInternet of Things (IoT)millimeter-wave (mmWave)trajectory planningbeamspace multiple-input multiple-output (MIMO)ElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2618, p 2618 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	unmanned aerial vehicle Internet of Things (IoT) millimeter-wave (mmWave) trajectory planning beamspace multiple-input multiple-output (MIMO) Electronics TK7800-8360
spellingShingle	unmanned aerial vehicle Internet of Things (IoT) millimeter-wave (mmWave) trajectory planning beamspace multiple-input multiple-output (MIMO) Electronics TK7800-8360 Xingxuan Zuo Lingfeng Shen Gangtao Han Xiaomin Mu Optimization of UAV-Aided Millimeter-Wave IoT Systems
description	Due to their maneuverability, unmanned aerial vehicles (UAVs) have grown into a promising enabler of the Internet of Things (IoTs). In addition to the benefits of the bandwidth and communication quality of millimeter-wave (mmWave) systems, a UAV-aided mmWave multiple-input and multiple-output (MIMO) communication system is investigated in this paper for the data collection of IoT systems, in which single-antenna IoT devices are divided into several clusters, and the UAV aided mmWave base station (UAV-BS) collects data from each cluster using the time division scheme. The joint optimization of the beam selection, UAV trajectory, user clustering, power allocation and transmission duration is studied in this paper to improve the data collection efficiency. The solution of the problem is then given in three steps. Firstly, the incremental <i>K</i>-means clustering and ant colony optimization algorithm are utilized to handle the UAV trajectory planning and user clustering problem. Secondly, an incremental beam selection scheme is employed to ensure that all the devices in each cluster can communicate with the UAV. Thirdly, an iterative algorithm is proposed by alternately optimizing the power allocation and transmission duration of the IoT devices. Finally, the simulation results demonstrate the effectiveness of the proposed solution for the UAV-aided mmWave communication system.
format	article
author	Xingxuan Zuo Lingfeng Shen Gangtao Han Xiaomin Mu
author_facet	Xingxuan Zuo Lingfeng Shen Gangtao Han Xiaomin Mu
author_sort	Xingxuan Zuo
title	Optimization of UAV-Aided Millimeter-Wave IoT Systems
title_short	Optimization of UAV-Aided Millimeter-Wave IoT Systems
title_full	Optimization of UAV-Aided Millimeter-Wave IoT Systems
title_fullStr	Optimization of UAV-Aided Millimeter-Wave IoT Systems
title_full_unstemmed	Optimization of UAV-Aided Millimeter-Wave IoT Systems
title_sort	optimization of uav-aided millimeter-wave iot systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bd530ac0d37442189ce8e6045a7adbdf
work_keys_str_mv	AT xingxuanzuo optimizationofuavaidedmillimeterwaveiotsystems AT lingfengshen optimizationofuavaidedmillimeterwaveiotsystems AT gangtaohan optimizationofuavaidedmillimeterwaveiotsystems AT xiaominmu optimizationofuavaidedmillimeterwaveiotsystems
_version_	1718434823894204416

Optimization of UAV-Aided Millimeter-Wave IoT Systems

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