Signal stripping based sensing parameter estimation in perceptive mobile networks

Zhang, JA; Huang, X; Guo, YJ; Rahman, ML

Signal stripping based sensing parameter estimation in perceptive mobile networks

Zhang, JA

Huang, X

Guo, YJ

Rahman, ML

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Publication Type:: Conference Proceeding
Citation:: 2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2017, 2017, 2017-January pp. 67 - 70
Issue Date:: 2017-10-06

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Field	Value	Language
dc.contributor.author	Zhang, JA https://orcid.org/0000-0002-6102-3762	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.contributor.author	Guo, YJ https://orcid.org/0000-0001-6008-9682	en_US
dc.contributor.author	Rahman, ML	en_US
dc.date.issued	2017-10-06	en_US
dc.identifier.citation	2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2017, 2017, 2017-January pp. 67 - 70	en_US
dc.identifier.isbn	9781509044542	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121770
dc.description.abstract	© 2017 IEEE. We propose signal stripping based approaches for estimating detailed channel composition parameters for sensing in the recently proposed perceptive mobile networks where simultaneous communication and radar sensing is performed. Via reconstructing a (differentiated) channel matrix, we obtain a signal model which can be solved by conventional compressive sensing (CS) techniques. Parameter estimation methods based on a 1-D CS algorithm are proposed and their effectiveness is validated by provided simulation results.	en_US
dc.relation.ispartof	2017 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2017	en_US
dc.relation.isbasedon	10.1109/APWC.2017.8062243	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Signal stripping based sensing parameter estimation in perceptive mobile networks	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-January	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
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-January	en_US

Abstract:

© 2017 IEEE. We propose signal stripping based approaches for estimating detailed channel composition parameters for sensing in the recently proposed perceptive mobile networks where simultaneous communication and radar sensing is performed. Via reconstructing a (differentiated) channel matrix, we obtain a signal model which can be solved by conventional compressive sensing (CS) techniques. Parameter estimation methods based on a 1-D CS algorithm are proposed and their effectiveness is validated by provided simulation results.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/121770