A fuzzy Q-learning approach for enhanced intercell interference coordination in LTE-Advanced heterogeneous networks

Daeinabi, A; Sandrasegaran, K

A fuzzy Q-learning approach for enhanced intercell interference coordination in LTE-Advanced heterogeneous networks

Daeinabi, A Sandrasegaran, K

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 20th Asia-Pacific Conference on Communication, APCC 2014, 2015, pp. 139 - 144
Issue Date:: 2015-04-22

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Field	Value	Language
dc.contributor.author	Daeinabi, A	en_US
dc.contributor.author	Sandrasegaran, K https://orcid.org/0000-0003-1270-5756	en_US
dc.date.issued	2015-04-22	en_US
dc.identifier.citation	Proceedings of the 20th Asia-Pacific Conference on Communication, APCC 2014, 2015, pp. 139 - 144	en_US
dc.identifier.isbn	9781479964352	en_US
dc.identifier.uri	http://hdl.handle.net/10453/34548
dc.description.abstract	© 2014 IEEE. Since the transmission power of macro eNodeB (eNB) is higher than pico eNB in long term evolution-advanced heterogeneous network, the coverage area of picocell is small. In order to address the coverage problem, cell range expansion (CRE) technique has been recently proposed. However, CRE can lead to the downlink interference problem on both data and control channels when users are connected to pico eNB. In order to mitigate the downlink interference problem, a new dynamic almost blank subframe (ABS) scheme is proposed in this paper. In this scheme, a fuzzy q-learning approach is used to find the optimum ABS value. Simulation results show that the system performance can be improved through the proposed scheme.	en_US
dc.relation.ispartof	Proceedings of the 20th Asia-Pacific Conference on Communication, APCC 2014	en_US
dc.relation.isbasedon	10.1109/APCC.2014.7091620	en_US
dc.title	A fuzzy Q-learning approach for enhanced intercell interference coordination in LTE-Advanced heterogeneous networks	en_US
dc.type	Conference Proceeding
utslib.for	0805 Distributed Computing	en_US
dc.location.activity	Pattaya, Thailand
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	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. Since the transmission power of macro eNodeB (eNB) is higher than pico eNB in long term evolution-advanced heterogeneous network, the coverage area of picocell is small. In order to address the coverage problem, cell range expansion (CRE) technique has been recently proposed. However, CRE can lead to the downlink interference problem on both data and control channels when users are connected to pico eNB. In order to mitigate the downlink interference problem, a new dynamic almost blank subframe (ABS) scheme is proposed in this paper. In this scheme, a fuzzy q-learning approach is used to find the optimum ABS value. Simulation results show that the system performance can be improved through the proposed scheme.

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http://hdl.handle.net/10453/34548