Multiple Signal Classification Based Joint Communication and Sensing System

Chen, X; Feng, Z; Wei, Z; Yuan, X; Zhang, P; Zhang, JA; Yang, H

Multiple Signal Classification Based Joint Communication and Sensing System

Chen, X Feng, Z Wei, Z Yuan, X

Zhang, P Zhang, JA Yang, H

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Wireless Communications, 2023, 22, (10), pp. 6504-6517
Issue Date:: 2023-10-01

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Field	Value	Language
dc.contributor.author	Chen, X
dc.contributor.author	Feng, Z
dc.contributor.author	Wei, Z
dc.contributor.author	Yuan, X https://orcid.org/0000-0002-9167-1613
dc.contributor.author	Zhang, P
dc.contributor.author	Zhang, JA
dc.contributor.author	Yang, H
dc.date.accessioned	2024-03-27T02:29:43Z
dc.date.available	2024-03-27T02:29:43Z
dc.date.issued	2023-10-01
dc.identifier.citation	IEEE Transactions on Wireless Communications, 2023, 22, (10), pp. 6504-6517
dc.identifier.issn	1536-1276
dc.identifier.issn	1558-2248
dc.identifier.uri	http://hdl.handle.net/10453/177235
dc.description.abstract	Joint communication and sensing (JCS) has become a promising technology for mobile networks because of its higher spectrum and energy efficiency. Up to now, the prevalent fast Fourier transform (FFT)-based sensing method for mobile JCS networks is on-grid based, and the grid interval determines the resolution. Because the mobile network usually has limited consecutive OFDM symbols in a downlink (DL) time slot, the sensing accuracy is restricted by the limited resolution, especially for velocity estimation. In this paper, we propose a multiple signal classification (MUSIC)-based JCS system that can achieve higher sensing accuracy for the angle of arrival, range, and velocity estimation, compared with the traditional FFT-based JCS method. We further propose a JCS channel state information (CSI) enhancement method by leveraging the JCS sensing results. Finally, we derive a theoretical lower bound for sensing mean square error (MSE) by using perturbation analysis. Simulation results show that in terms of the sensing MSE performance, the proposed MUSIC-based JCS outperforms the FFT-based one by more than 20 dB. Moreover, the bit error rate (BER) of communication demodulation using the proposed JCS CSI enhancement method is significantly reduced compared with communication using the originally estimated CSI.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Wireless Communications
dc.relation.isbasedon	10.1109/TWC.2023.3244195
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	4008 Electrical engineering
dc.subject.classification	4606 Distributed computing and systems software
dc.title	Multiple Signal Classification Based Joint Communication and Sensing System
dc.type	Journal Article
utslib.citation.volume	22
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
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-27T02:29:42Z
pubs.issue	10
pubs.publication-status	Published
pubs.volume	22
utslib.citation.issue	10

Abstract:

Joint communication and sensing (JCS) has become a promising technology for mobile networks because of its higher spectrum and energy efficiency. Up to now, the prevalent fast Fourier transform (FFT)-based sensing method for mobile JCS networks is on-grid based, and the grid interval determines the resolution. Because the mobile network usually has limited consecutive OFDM symbols in a downlink (DL) time slot, the sensing accuracy is restricted by the limited resolution, especially for velocity estimation. In this paper, we propose a multiple signal classification (MUSIC)-based JCS system that can achieve higher sensing accuracy for the angle of arrival, range, and velocity estimation, compared with the traditional FFT-based JCS method. We further propose a JCS channel state information (CSI) enhancement method by leveraging the JCS sensing results. Finally, we derive a theoretical lower bound for sensing mean square error (MSE) by using perturbation analysis. Simulation results show that in terms of the sensing MSE performance, the proposed MUSIC-based JCS outperforms the FFT-based one by more than 20 dB. Moreover, the bit error rate (BER) of communication demodulation using the proposed JCS CSI enhancement method is significantly reduced compared with communication using the originally estimated CSI.

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http://hdl.handle.net/10453/177235