Waveform Optimization for MIMO Joint Communication and Radio Sensing Systems with Imperfect Channel Feedbacks

Yuan, X; Feng, Z; Ni, W; Wei, Z; Liu, RP

Waveform Optimization for MIMO Joint Communication and Radio Sensing Systems with Imperfect Channel Feedbacks

Yuan, X

Feng, Z Ni, W

Wei, Z Liu, RP

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2020 IEEE International Conference on Communications Workshops (ICC Workshops), 2020, 00, pp. 1-6
Issue Date:: 2020-07-21

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Field	Value	Language
dc.contributor.author	Yuan, X https://orcid.org/0000-0002-9167-1613
dc.contributor.author	Feng, Z
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Wei, Z
dc.contributor.author	Liu, RP
dc.date	2020-06-07
dc.date.accessioned	2021-04-14T21:17:03Z
dc.date.available	2021-04-14T21:17:03Z
dc.date.issued	2020-07-21
dc.identifier.citation	2020 IEEE International Conference on Communications Workshops (ICC Workshops), 2020, 00, pp. 1-6
dc.identifier.isbn	9781728174402
dc.identifier.uri	http://hdl.handle.net/10453/148112
dc.description.abstract	In this paper, we study optimal waveform design to maximize mutual information (MI) for a joint communication and (radio) sensing (JCAS, a.k.a., radar-communication) multi-input multi-output (MIMO) downlink system. We consider a typical packet-based signal structure which includes training and data symbols. We first derive the conditional MI for both sensing and communication under correlated channels by considering the training overhead and channel estimation error (CEE). Based on the derived MI, we provide optimal waveform design methods for three scenarios, including maximizing MI for communication only and for sensing only, and maximizing a weighted sum MI for both communication and sensing. We also present extensive simulation results that provide insights on waveform design and validate the effectiveness of the proposed designs.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2020 IEEE International Conference on Communications Workshops (ICC Workshops)
dc.relation.ispartof	2020 IEEE International Conference on Communications Workshops
dc.relation.isbasedon	10.1109/iccworkshops49005.2020.9145467
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Waveform Optimization for MIMO Joint Communication and Radio Sensing Systems with Imperfect Channel Feedbacks
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Dublin, Ireland
utslib.for	0805 Distributed Computing
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/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2021-04-14T21:17:02Z
pubs.finish-date	2020-06-11
pubs.publication-status	Published
pubs.start-date	2020-06-07
pubs.volume	00

Abstract:

In this paper, we study optimal waveform design to maximize mutual information (MI) for a joint communication and (radio) sensing (JCAS, a.k.a., radar-communication) multi-input multi-output (MIMO) downlink system. We consider a typical packet-based signal structure which includes training and data symbols. We first derive the conditional MI for both sensing and communication under correlated channels by considering the training overhead and channel estimation error (CEE). Based on the derived MI, we provide optimal waveform design methods for three scenarios, including maximizing MI for communication only and for sensing only, and maximizing a weighted sum MI for both communication and sensing. We also present extensive simulation results that provide insights on waveform design and validate the effectiveness of the proposed designs.

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http://hdl.handle.net/10453/148112