On-Demand Deployment of Aerial Base Stations for Coverage Enhancement in Reconfigurable Intelligent Surface-Assisted Cellular Networks on Uneven Terrains

Savkin, AV; Huang, C; Ni, W

On-Demand Deployment of Aerial Base Stations for Coverage Enhancement in Reconfigurable Intelligent Surface-Assisted Cellular Networks on Uneven Terrains

Savkin, AV Huang, C Ni, W

Permalink

Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Communications Letters, 2023, 27, (2), pp. 666-670
Issue Date:: 2023-02-01

Closed Access

	Filename	Description	Size
	On-Demand_Deployment_of_Aerial_Base_Stations_for_Coverage_Enhancement_in_Reconfigurable_Intelligent_Surface-Assisted_Cellular_Networks_on_Uneven_Terrains.pdf	Published version	879.01 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Savkin, AV
dc.contributor.author	Huang, C
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.date.accessioned	2024-04-17T01:10:20Z
dc.date.available	2024-04-17T01:10:20Z
dc.date.issued	2023-02-01
dc.identifier.citation	IEEE Communications Letters, 2023, 27, (2), pp. 666-670
dc.identifier.issn	1089-7798
dc.identifier.issn	1558-2558
dc.identifier.uri	http://hdl.handle.net/10453/177993
dc.description.abstract	This letter considers the problem of placing aerial base stations (BSs), also known as Unmanned Aerial Vehicle-based BSs (UAV-BSs), to communicate with ground users in cellular networks on uneven terrains. Reconfigurable Intelligent Surfaces (RISs) are deployed on the uneven terrains to assist with the UAV-BSs in eliminating coverage blind spots and extending coverage. Signals are transmitted by the UAV-BSs either directly or via RISs. We develop a new UAV-BS deployment algorithm to maximize coverage. The convergence of the algorithm is analyzed. Simulation results demonstrate the effectiveness of our algorithm.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	http://purl.org/au-research/grants/arc/DP190102501
dc.relation.ispartof	IEEE Communications Letters
dc.relation.isbasedon	10.1109/LCOMM.2022.3227922
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4606 Distributed computing and systems software
dc.title	On-Demand Deployment of Aerial Base Stations for Coverage Enhancement in Reconfigurable Intelligent Surface-Assisted Cellular Networks on Uneven Terrains
dc.type	Journal Article
utslib.citation.volume	27
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-04-17T01:10:18Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	27
utslib.citation.issue	2

Abstract:

This letter considers the problem of placing aerial base stations (BSs), also known as Unmanned Aerial Vehicle-based BSs (UAV-BSs), to communicate with ground users in cellular networks on uneven terrains. Reconfigurable Intelligent Surfaces (RISs) are deployed on the uneven terrains to assist with the UAV-BSs in eliminating coverage blind spots and extending coverage. Signals are transmitted by the UAV-BSs either directly or via RISs. We develop a new UAV-BS deployment algorithm to maximize coverage. The convergence of the algorithm is analyzed. Simulation results demonstrate the effectiveness of our algorithm.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/177993