Compressed sensing based channel estimation for two-way relay networks

Cheng, P; Gui, L; Rui, Y; Guo, YJ; Huang, X; Zhang, W

Compressed sensing based channel estimation for two-way relay networks

Cheng, P Gui, L Rui, Y Guo, YJ

Huang, X

Zhang, W

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Publication Type:: Journal Article
Citation:: IEEE Wireless Communications Letters, 2012, 1 (3), pp. 201 - 204
Issue Date:: 2012-06-01

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Field	Value	Language
dc.contributor.author	Cheng, P	en_US
dc.contributor.author	Gui, L	en_US
dc.contributor.author	Rui, Y	en_US
dc.contributor.author	Guo, YJ https://orcid.org/0000-0001-6008-9682	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.contributor.author	Zhang, W	en_US
dc.date.issued	2012-06-01	en_US
dc.identifier.citation	IEEE Wireless Communications Letters, 2012, 1 (3), pp. 201 - 204	en_US
dc.identifier.issn	2162-2337	en_US
dc.identifier.uri	http://hdl.handle.net/10453/113872
dc.description.abstract	In this letter, a novel channel estimation scheme based on compressed sensing (CS) theory is proposed for two-way relay networks (TWRN) in sparse frequency-selective fading channels. Unlike point-to-point systems, applying CS theory to sparse channel estimation in TWRN is much more challenging since the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. To solve this problem, instead of directly estimating the equivalent channels, a linear precoding based method is designed to firstly separate the individual channels between the terminals and the relay from the equivalent channels. CS theory is then applied to the time-domain channel estimation with much smaller number of pilot symbols. This scheme enables accurate channel estimation for TWRN with significant overhead reduction. Extensive numerical results are provided to substantiate the effectiveness of the proposed method. © 2012 IEEE.	en_US
dc.relation.ispartof	IEEE Wireless Communications Letters	en_US
dc.relation.isbasedon	10.1109/WCL.2012.031512.120083	en_US
dc.title	Compressed sensing based channel estimation for two-way relay networks	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	1	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0906 Electrical and Electronic Engineering	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	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

In this letter, a novel channel estimation scheme based on compressed sensing (CS) theory is proposed for two-way relay networks (TWRN) in sparse frequency-selective fading channels. Unlike point-to-point systems, applying CS theory to sparse channel estimation in TWRN is much more challenging since the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. To solve this problem, instead of directly estimating the equivalent channels, a linear precoding based method is designed to firstly separate the individual channels between the terminals and the relay from the equivalent channels. CS theory is then applied to the time-domain channel estimation with much smaller number of pilot symbols. This scheme enables accurate channel estimation for TWRN with significant overhead reduction. Extensive numerical results are provided to substantiate the effectiveness of the proposed method. © 2012 IEEE.

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http://hdl.handle.net/10453/113872