A coloring-based resource allocation for OFDMA femtocell networks

Zhang, Q; Zhu, X; Wu, L; Sandrasegaran, K

A coloring-based resource allocation for OFDMA femtocell networks

Zhang, Q Zhu, X Wu, L

Sandrasegaran, K

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Publication Type:: Conference Proceeding
Citation:: IEEE Wireless Communications and Networking Conference, WCNC, 2013, pp. 673 - 678
Issue Date:: 2013-08-21

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Field	Value	Language
dc.contributor.author	Zhang, Q	en_US
dc.contributor.author	Zhu, X	en_US
dc.contributor.author	Wu, L https://orcid.org/0000-0002-8577-0367	en_US
dc.contributor.author	Sandrasegaran, K https://orcid.org/0000-0003-1270-5756	en_US
dc.date.issued	2013-08-21	en_US
dc.identifier.citation	IEEE Wireless Communications and Networking Conference, WCNC, 2013, pp. 673 - 678	en_US
dc.identifier.isbn	9781467359399	en_US
dc.identifier.issn	1525-3511	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28456
dc.description.abstract	In order to improve the spectrum efficiency in the femtocell network and mitigate the co-tier/cross-tier interference, we propose a novel graph-theoretic scheme based on coloring algorithm for self-adaptive spectrum resource allocation in femtocells. A dynamic orthogonal spectrum sharing between macrocell and femtocell is utilized in the proposed allocation scheme to reduce the cross-tier interference. In order to mitigate the co-tier interference, a graph-based clustering resource allocation (GCRA) scheme is presented. The interference graph of the femto-tier is built first based on the measurement reports of femtocell user equipments (FUEs). Then a coloring algorithm is implemented in a distributed way to construct disjoint clusters in which the frequency band can be reused to improve the spectrum efficiency. Finally, a dynamic orthogonal resource allocation is performed to avoid the inter-cluster interference. The simulation results reveal that the GCRA approach enhances the spectrum efficiency of the femtocell network, while mitigating the cotier/ cross-tier interference of the heterogeneous network. © 2013 IEEE.	en_US
dc.relation.ispartof	IEEE Wireless Communications and Networking Conference, WCNC	en_US
dc.relation.isbasedon	10.1109/WCNC.2013.6554644	en_US
dc.title	A coloring-based resource allocation for OFDMA femtocell networks	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
dc.location.activity	Shanghai, China	en_US
dc.location.activity	Shanghai, PEOPLES R CHINA
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 - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In order to improve the spectrum efficiency in the femtocell network and mitigate the co-tier/cross-tier interference, we propose a novel graph-theoretic scheme based on coloring algorithm for self-adaptive spectrum resource allocation in femtocells. A dynamic orthogonal spectrum sharing between macrocell and femtocell is utilized in the proposed allocation scheme to reduce the cross-tier interference. In order to mitigate the co-tier interference, a graph-based clustering resource allocation (GCRA) scheme is presented. The interference graph of the femto-tier is built first based on the measurement reports of femtocell user equipments (FUEs). Then a coloring algorithm is implemented in a distributed way to construct disjoint clusters in which the frequency band can be reused to improve the spectrum efficiency. Finally, a dynamic orthogonal resource allocation is performed to avoid the inter-cluster interference. The simulation results reveal that the GCRA approach enhances the spectrum efficiency of the femtocell network, while mitigating the cotier/ cross-tier interference of the heterogeneous network. © 2013 IEEE.

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http://hdl.handle.net/10453/28456