Learning-Assisted Clustered Access of 5G/B5G Networks to Unlicensed Spectrum

Cui, Q; Ni, W; Li, S; Zhao, B; Liu, RP; Zhang, P

Learning-Assisted Clustered Access of 5G/B5G Networks to Unlicensed Spectrum

Cui, Q Ni, W

Li, S Zhao, B Liu, RP Zhang, P

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Wireless Communications, 2020, 27, (1), pp. 31-37
Issue Date:: 2020-02-01

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Field	Value	Language
dc.contributor.author	Cui, Q
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Li, S
dc.contributor.author	Zhao, B
dc.contributor.author	Liu, RP
dc.contributor.author	Zhang, P
dc.date.accessioned	2021-03-20T23:56:59Z
dc.date.available	2021-03-20T23:56:59Z
dc.date.issued	2020-02-01
dc.identifier.citation	IEEE Wireless Communications, 2020, 27, (1), pp. 31-37
dc.identifier.issn	1536-1284
dc.identifier.issn	1558-0687
dc.identifier.uri	http://hdl.handle.net/10453/147398
dc.description.abstract	© 2002-2012 IEEE. License-assisted access (LAA) to unlicensed spectrum is a potential solution to improve the resource availability and system scalability of 5G/B5G networks. Challenges arise from coexistence between LAA and incumbent systems, especially the ubiquitous IEEE 802.11 WiFi systems. This article demonstrates that the coexistence can be substantially improved by leveraging learning-based clustering of small base stations (SBSs), referred to as learning-assisted clustered access (LACA), and improving the interoperability between licensed and unlicensed access. Fast signaling and a centralized control plane of licensed access can facilitate clustering SBSs for coordinated access to the unlicensed spectrum, hence reducing the number of parties contending for access and alleviating contention. Appropriate clustering of SBSs is important to the efficiency of LACA in 5G/B5G networks. LACA can quickly converge with strong locality, facilitating the coordination of the SBSs, for example, cooperatively connecting multiple users and conducting beamforming. Analytic evaluation and numerical tests confirm the improved coexistence through enlarged LAA-WiFi capacity regions, as well as reduced transmission delays.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Wireless Communications
dc.relation.isbasedon	10.1109/MWC.001.1900293
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
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.title	Learning-Assisted Clustered Access of 5G/B5G Networks to Unlicensed Spectrum
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	*
pubs.consider-herdc	false
dc.date.updated	2021-03-20T23:56:56Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	27
utslib.citation.issue	1

Abstract:

© 2002-2012 IEEE. License-assisted access (LAA) to unlicensed spectrum is a potential solution to improve the resource availability and system scalability of 5G/B5G networks. Challenges arise from coexistence between LAA and incumbent systems, especially the ubiquitous IEEE 802.11 WiFi systems. This article demonstrates that the coexistence can be substantially improved by leveraging learning-based clustering of small base stations (SBSs), referred to as learning-assisted clustered access (LACA), and improving the interoperability between licensed and unlicensed access. Fast signaling and a centralized control plane of licensed access can facilitate clustering SBSs for coordinated access to the unlicensed spectrum, hence reducing the number of parties contending for access and alleviating contention. Appropriate clustering of SBSs is important to the efficiency of LACA in 5G/B5G networks. LACA can quickly converge with strong locality, facilitating the coordination of the SBSs, for example, cooperatively connecting multiple users and conducting beamforming. Analytic evaluation and numerical tests confirm the improved coexistence through enlarged LAA-WiFi capacity regions, as well as reduced transmission delays.

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

http://hdl.handle.net/10453/147398