Distributed link clustering for clustered cooperative MIMO

Sung, CK; Zhang, JA; Chen, Z; Collings, IB

Distributed link clustering for clustered cooperative MIMO

Sung, CK Zhang, JA

Chen, Z Collings, IB

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Publication Type:: Conference Proceeding
Citation:: IEEE Vehicular Technology Conference, 2014, 2015-January (January)
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Sung, CK	en_US
dc.contributor.author	Zhang, JA https://orcid.org/0000-0002-6102-3762	en_US
dc.contributor.author	Chen, Z	en_US
dc.contributor.author	Collings, IB	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	IEEE Vehicular Technology Conference, 2014, 2015-January (January)	en_US
dc.identifier.issn	1550-2252	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121351
dc.description.abstract	© 2014 IEEE. In the cooperative multiple-input/multiple-output (MIMO), multiple access point (AP)-user links form a cluster to increase achievable throughput by cooperatively mitigating inter-user interference within the cluster. In this paper, we propose a clustered cooperative MIMO endowing a constraint on the cluster size such that the clustered MIMO can be implemented as a distributed version of downlink multiuser MIMO in existing standards with minimal modifications. New greedy algorithm and coalition formation algorithm are proposed using matching theory for establishing clusters and allocating frequencies. Simulation results shows that the proposed algorithms achieve almost 20% higher throughput than the fixed cell planning scheme, with very low searching complexity.	en_US
dc.relation.ispartof	IEEE Vehicular Technology Conference	en_US
dc.relation.isbasedon	10.1109/VTCSpring.2014.7022885	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Distributed link clustering for clustered cooperative MIMO	en_US
dc.type	Conference Proceeding
utslib.citation.volume	January	en_US
utslib.citation.volume	2015-January	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
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
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.issue	January	en_US
pubs.publication-status	Published	en_US
pubs.volume	2015-January	en_US

Abstract:

© 2014 IEEE. In the cooperative multiple-input/multiple-output (MIMO), multiple access point (AP)-user links form a cluster to increase achievable throughput by cooperatively mitigating inter-user interference within the cluster. In this paper, we propose a clustered cooperative MIMO endowing a constraint on the cluster size such that the clustered MIMO can be implemented as a distributed version of downlink multiuser MIMO in existing standards with minimal modifications. New greedy algorithm and coalition formation algorithm are proposed using matching theory for establishing clusters and allocating frequencies. Simulation results shows that the proposed algorithms achieve almost 20% higher throughput than the fixed cell planning scheme, with very low searching complexity.

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http://hdl.handle.net/10453/121351