Modified elite chaotic artificial fish swarm algorithm for PAPR reduction in OFDM systems

Zhou, J; Dutkiewicz, E; Liu, RP; Huang, X; Fang, G; Liu, Y

Modified elite chaotic artificial fish swarm algorithm for PAPR reduction in OFDM systems

Zhou, J Dutkiewicz, E

Liu, RP

Huang, X

Fang, G Liu, Y

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Publication Type:: Conference Proceeding
Citation:: 14th International Symposium on Communications and Information Technologies, ISCIT 2014, 2015, pp. 503 - 507
Issue Date:: 2015-01-15

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Field	Value	Language
dc.contributor.author	Zhou, J	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Liu, RP https://orcid.org/0000-0001-7001-6305	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.contributor.author	Fang, G	en_US
dc.contributor.author	Liu, Y	en_US
dc.date.issued	2015-01-15	en_US
dc.identifier.citation	14th International Symposium on Communications and Information Technologies, ISCIT 2014, 2015, pp. 503 - 507	en_US
dc.identifier.isbn	9781479944163	en_US
dc.identifier.uri	http://hdl.handle.net/10453/34553
dc.description.abstract	© 2014 IEEE. Orthogonal frequency division multiplexing (OFDM) is a leading technology in the field of broadband wireless communications. In OFDM systems, a high peak-to-average power ratio (PAPR) is a critical issue, which may cause a nonlinear distortion and reduce power efficiency. To reduce the PAPR, partial transmit sequences (PTS) technique can be applied to the transmit data. However, the phase factor sequence selection in PTS technique is a non-linear optimization problem and it suffers from high complexity and memory use when there is a large number of non-overlapping sub-blocks in one symbol. In this paper a novel modified elite chaotic artificial fish swarm algorithm for PTS method (MECAFSA-PTS) is proposed to generate the optimum phase factors. The MECAFSA-PTS method is evaluated with extensive simulations and its performance is compared with quantum evolutionary and selective mapping algorithms. Our results show that the proposed MECAFSA-PTS algorithm is efficient in PAPR reduction.	en_US
dc.relation.ispartof	14th International Symposium on Communications and Information Technologies, ISCIT 2014	en_US
dc.relation.isbasedon	10.1109/ISCIT.2014.7011964	en_US
dc.title	Modified elite chaotic artificial fish swarm algorithm for PAPR reduction in OFDM systems	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
utslib.for	0906 Electrical and Electronic Engineering	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	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. Orthogonal frequency division multiplexing (OFDM) is a leading technology in the field of broadband wireless communications. In OFDM systems, a high peak-to-average power ratio (PAPR) is a critical issue, which may cause a nonlinear distortion and reduce power efficiency. To reduce the PAPR, partial transmit sequences (PTS) technique can be applied to the transmit data. However, the phase factor sequence selection in PTS technique is a non-linear optimization problem and it suffers from high complexity and memory use when there is a large number of non-overlapping sub-blocks in one symbol. In this paper a novel modified elite chaotic artificial fish swarm algorithm for PTS method (MECAFSA-PTS) is proposed to generate the optimum phase factors. The MECAFSA-PTS method is evaluated with extensive simulations and its performance is compared with quantum evolutionary and selective mapping algorithms. Our results show that the proposed MECAFSA-PTS algorithm is efficient in PAPR reduction.

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http://hdl.handle.net/10453/34553