Sparse channel estimation for OFDM transmission over two-way works

Cheng, P; Gui, L; Tao, M; Guo, YJ; Huang, X; Rui, Y

Sparse channel estimation for OFDM transmission over two-way works

Cheng, P Gui, L Tao, M Guo, YJ

Huang, X

Rui, Y

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Communications, 2012, pp. 3948 - 3953
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Cheng, P	en_US
dc.contributor.author	Gui, L	en_US
dc.contributor.author	Tao, M	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	Rui, Y	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	IEEE International Conference on Communications, 2012, pp. 3948 - 3953	en_US
dc.identifier.isbn	9781457720529	en_US
dc.identifier.issn	1550-3607	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119625
dc.description.abstract	Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. CS enables the recovery of high-dimensional sparse signals from much fewer samples than usually required. Further, quite a few recent channel measurement experiments show that many wireless channels also tend to exhibit sparsity. In this case, CS theory can be applicable to sparse channel estimation and its effectiveness has been validated in point-to-point (P2P) communication. In this work, we study sparse channel estimation for two-way relay networks (TWRN). Unlike P2P systems, applying CS theory to sparse channel estimation in TWRN is much more challenging. One issue is that the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. On this basis, novel schemes are proposed to solve this problem and effectively improve the accuracy of TWRN channel estimation when using CS theory. Extensive numerical results are provided to corroborate the proposed studies. © 2012 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Communications	en_US
dc.relation.isbasedon	10.1109/ICC.2012.6364641	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Sparse channel estimation for OFDM transmission over two-way works	en_US
dc.type	Conference Proceeding
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.publication-status	Published	en_US

Abstract:

Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. CS enables the recovery of high-dimensional sparse signals from much fewer samples than usually required. Further, quite a few recent channel measurement experiments show that many wireless channels also tend to exhibit sparsity. In this case, CS theory can be applicable to sparse channel estimation and its effectiveness has been validated in point-to-point (P2P) communication. In this work, we study sparse channel estimation for two-way relay networks (TWRN). Unlike P2P systems, applying CS theory to sparse channel estimation in TWRN is much more challenging. One issue is that the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. On this basis, novel schemes are proposed to solve this problem and effectively improve the accuracy of TWRN channel estimation when using CS theory. Extensive numerical results are provided to corroborate the proposed studies. © 2012 IEEE.

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http://hdl.handle.net/10453/119625