Introducing User Grouping to Counteract Channel Correlation in IRS-Assisted ISAC

Chen, J; Zhu, K; Wu, K; Niu, J; Zhang, JA

Introducing User Grouping to Counteract Channel Correlation in IRS-Assisted ISAC

Chen, J Zhu, K Wu, K

Niu, J Zhang, JA

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Communications Letters, 2024, 28, (4), pp. 808-812
Issue Date:: 2024-04-01

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Field	Value	Language
dc.contributor.author	Chen, J
dc.contributor.author	Zhu, K
dc.contributor.author	Wu, K https://orcid.org/0000-0003-1298-6404
dc.contributor.author	Niu, J
dc.contributor.author	Zhang, JA
dc.date.accessioned	2024-08-07T04:52:32Z
dc.date.available	2024-08-07T04:52:32Z
dc.date.issued	2024-04-01
dc.identifier.citation	IEEE Communications Letters, 2024, 28, (4), pp. 808-812
dc.identifier.issn	1089-7798
dc.identifier.issn	1558-2558
dc.identifier.uri	http://hdl.handle.net/10453/180242
dc.description.abstract	Intelligent reflective surface (IRS) assisted integrated sensing and communications (ISAC) is a promising technology for future mobile communications. However, high channel correlation, which may significantly degrade the performance of ISAC, has been overlooked. This letter addresses the issue by introducing user grouping to IRS-assisted ISAC. We design a novel user grouping scheme to minimize intra-group channel correlation. We also derive the asymptotically optimal number of user groups. Moreover, for any user group, we provide a joint base station and IRS beamforming design by applying the alternative optimization strategy, together with the weighted minimum mean squared error and discrete phase shift optimization techniques. Simulation results demonstrate substantial performance enhancement brought by user grouping to IRS-assisted ISAC.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Communications Letters
dc.relation.isbasedon	10.1109/LCOMM.2024.3368336
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4606 Distributed computing and systems software
dc.title	Introducing User Grouping to Counteract Channel Correlation in IRS-Assisted ISAC
dc.type	Journal Article
utslib.citation.volume	28
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
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
pubs.organisational-group	University of Technology Sydney/All Manual Groups
pubs.organisational-group	University of Technology Sydney/All Manual Groups/Global Big Data Technologies Research Centre (GBDTC)
utslib.copyright.status	closed_access	*
dc.date.updated	2024-08-07T04:52:29Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	28
utslib.citation.issue	4

Abstract:

Intelligent reflective surface (IRS) assisted integrated sensing and communications (ISAC) is a promising technology for future mobile communications. However, high channel correlation, which may significantly degrade the performance of ISAC, has been overlooked. This letter addresses the issue by introducing user grouping to IRS-assisted ISAC. We design a novel user grouping scheme to minimize intra-group channel correlation. We also derive the asymptotically optimal number of user groups. Moreover, for any user group, we provide a joint base station and IRS beamforming design by applying the alternative optimization strategy, together with the weighted minimum mean squared error and discrete phase shift optimization techniques. Simulation results demonstrate substantial performance enhancement brought by user grouping to IRS-assisted ISAC.

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http://hdl.handle.net/10453/180242