Reference : Resource Allocation for UAV Relay-Assisted IoT Communication Networks

	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/44425

Title :	Resource Allocation for UAV Relay-Assisted IoT Communication Networks
Language :	English
Translated title :	[en] Resource Allocation for UAV Relay-Assisted IoT Communication Networks
Author, co-author :	Tran Dinh, Hieu [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Nguyen, van Dinh [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Gautam, Sumit [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Vu, Thang Xuan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	6-Oct-2020
Number of pages :	7
Reviewed work :	This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data from IoT devices and transfer information to a ground gateway (GW). In this context, we jointly optimize the allocated bandwidth, transmission power, as well as the UAV trajectory to maximize the total system throughput while satisfying the user's latency requirement and the UAV's limited storage capacity. The formulated problem is strongly non-convex which is very challenging to solve optimally. Towards an appealing solution, we first introduce new variables to convert the original problem into a computationally tractable form, and then develop an iterative algorithm for its solution by leveraging the inner approximation method. Numerical results are given to show significant performance improvement over benchmark schemes.
Peer reviewed :	Yes
On invitation :	Yes
Audience :	International
Event name :	IEEE GLOBECOM 2020 - Workshop on Future of Wireless Access for Industrial IoT (FutureIIoT)
Event date :	7-12-2020
Event organizer :	IEEE Comsoc
Event place (city) :	Taipei
Event country :	Taiwan
Keywords :	[en] Information freshness ; Internet of Things ; timely data collection ; unmanned aerial vehicle (UAV).
Abstract :	[en] This work studies unmanned aerial vehicle (UAV) relay-assisted Internet of Things (IoT) communication networks in which a UAV is deployed as an aerial base station (BS) to collect time-constrained data from IoT devices and transfer information to a ground gateway (GW). In this context, we jointly optimize the allocated bandwidth, transmission power, as well as the UAV trajectory to maximize the total system throughput while satisfying the user’s latency requirement and the UAV’s limited storage capacity. The formulated problem is strongly nonconvex which is very challenging to solve optimally. Towards an appealing solution, we first introduce new variables to convert the original problem into a computationally tractable form, and then develop an iterative algorithm for its solution by leveraging the inner approximation method. Numerical results are given to show
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Funders :	Luxembourg National Research Fund under project FNR CORE ProCAST, grant C17/IS/11691338 and FNR CORE 5G-Sky, grant C19/IS/13713801
Name of the research project :	FNR CORE ProCAST, grant C17/IS/11691338 and FNR CORE 5G-Sky, grant C19/IS/13713801
Target :	Researchers ; Students ; General public
Permalink :	http://hdl.handle.net/10993/44425
FnR project :	FnR ; FNR11691338 > Bjorn Ottersten > ProCAST > Proactive Edge Caching for Content Delivery Networks powered by Hybrid Satellite/Terrestrial Backhauling > 01/07/2018 > 30/06/2021 > 2017

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