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Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges

The cognitive radio is an emerging technology that enables dynamic spectrum access in wireless networks. The cognitive radio is capable of opportunistically using the available portions of a licensed spectrum to improve the application performance for unlicensed users. The opportunistic use of the a...

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Main Authors:	Ahmed, Ejaz, Gani, Abdullah, Abolfazli, Saeid, Yao, Liu Jie, Khan, Samee U.
Format:	Article
Published:	Institute of Electrical and Electronics Engineers (IEEE) 2016
Subjects:	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.um.edu.my/17889/ http://dx.doi.org/10.1109/COMST.2014.2363082
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spelling	my.um.eprints.178892018-10-12T02:58:24Z http://eprints.um.edu.my/17889/ Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges Ahmed, Ejaz Gani, Abdullah Abolfazli, Saeid Yao, Liu Jie Khan, Samee U. QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering The cognitive radio is an emerging technology that enables dynamic spectrum access in wireless networks. The cognitive radio is capable of opportunistically using the available portions of a licensed spectrum to improve the application performance for unlicensed users. The opportunistic use of the available channels in the wireless environment requires dynamic channel assignment to efficiently utilize the available resources while minimizing the interference in the network. A challenging aspect of such algorithms is the incorporation of the channels' diverse characteristics, highly dynamic network conditions with respect to primary users' activity, and different fragmented sizes of the available channels. This paper presents a comprehensive survey on the state-of-the-art channel assignment algorithms in cognitive radio networks. We also classify the algorithms by presenting a thematic taxonomy of the current channel assignment algorithms in cognitive radio networks. Moreover, the critical aspects of the current channel assignment algorithms in cognitive radio networks are analyzed to determine the strengths and weaknesses of such algorithms. The similarities and differences of the algorithms based on the important parameters, such as routing dependencies, channel models, assignment methods, execution model, and optimization objectives, are also investigated. We also discuss open research issues and challenges of channel assignment in the cognitive radio networks. Institute of Electrical and Electronics Engineers (IEEE) 2016 Article PeerReviewed Ahmed, Ejaz and Gani, Abdullah and Abolfazli, Saeid and Yao, Liu Jie and Khan, Samee U. (2016) Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges. IEEE Communications Surveys & Tutorials, 18 (1). pp. 795-823. ISSN 1553-877X http://dx.doi.org/10.1109/COMST.2014.2363082 doi:10.1109/COMST.2014.2363082
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering Ahmed, Ejaz Gani, Abdullah Abolfazli, Saeid Yao, Liu Jie Khan, Samee U. Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
description	The cognitive radio is an emerging technology that enables dynamic spectrum access in wireless networks. The cognitive radio is capable of opportunistically using the available portions of a licensed spectrum to improve the application performance for unlicensed users. The opportunistic use of the available channels in the wireless environment requires dynamic channel assignment to efficiently utilize the available resources while minimizing the interference in the network. A challenging aspect of such algorithms is the incorporation of the channels' diverse characteristics, highly dynamic network conditions with respect to primary users' activity, and different fragmented sizes of the available channels. This paper presents a comprehensive survey on the state-of-the-art channel assignment algorithms in cognitive radio networks. We also classify the algorithms by presenting a thematic taxonomy of the current channel assignment algorithms in cognitive radio networks. Moreover, the critical aspects of the current channel assignment algorithms in cognitive radio networks are analyzed to determine the strengths and weaknesses of such algorithms. The similarities and differences of the algorithms based on the important parameters, such as routing dependencies, channel models, assignment methods, execution model, and optimization objectives, are also investigated. We also discuss open research issues and challenges of channel assignment in the cognitive radio networks.
format	Article
author	Ahmed, Ejaz Gani, Abdullah Abolfazli, Saeid Yao, Liu Jie Khan, Samee U.
author_facet	Ahmed, Ejaz Gani, Abdullah Abolfazli, Saeid Yao, Liu Jie Khan, Samee U.
author_sort	Ahmed, Ejaz
title	Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
title_short	Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
title_full	Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
title_fullStr	Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
title_full_unstemmed	Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
title_sort	channel assignment algorithms in cognitive radio networks: taxonomy, open issues, and challenges
publisher	Institute of Electrical and Electronics Engineers (IEEE)
publishDate	2016
url	http://eprints.um.edu.my/17889/ http://dx.doi.org/10.1109/COMST.2014.2363082
_version_	1643690547850772480
score	13.211869

Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges

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