Uplink Sensing Using CSI Ratio in Perceptive Mobile Networks

Ni, Z; Zhang, JA; Wu, K; Liu, RP

Uplink Sensing Using CSI Ratio in Perceptive Mobile Networks

Ni, Z

Zhang, JA Wu, K

Liu, RP

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Signal Processing, 2023, 71, pp. 2699-2712
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Ni, Z https://orcid.org/0000-0002-7932-5996
dc.contributor.author	Zhang, JA
dc.contributor.author	Wu, K https://orcid.org/0000-0003-1298-6404
dc.contributor.author	Liu, RP
dc.date.accessioned	2024-03-27T02:36:54Z
dc.date.available	2024-03-27T02:36:54Z
dc.date.issued	2023-01-01
dc.identifier.citation	IEEE Transactions on Signal Processing, 2023, 71, pp. 2699-2712
dc.identifier.issn	1053-587X
dc.identifier.issn	1941-0476
dc.identifier.uri	http://hdl.handle.net/10453/177239
dc.description.abstract	Uplink sensing in perceptive mobile networks (PMNs), which uses uplink communication signals for sensing the environment around a base station, faces challenging issues of clock asynchronism and the requirement of a line-of-sight (LOS) path between transmitters and receivers. The channel state information (CSI) ratio has been applied to resolve these issues, however, current research on the CSI ratio is limited to Doppler estimation in a single dynamic path. This paper proposes an advanced parameter estimation scheme that can extract multiple dynamic parameters, including Doppler frequency, angle-of-arrival (AoA), and delay, in a communication uplink channel and completes the localization of multiple moving targets. Our scheme is based on the multi-element complex Taylor series of the CSI ratio that converts a nonlinear function of sensing parameters to linear forms and enables the applications of traditional sensing algorithms. Using the truncated Taylor series, we develop novel multiple-signal-classification grid searching algorithms for estimating Doppler frequencies and AoAs and use the least-square method to obtain delays. Both experimental and simulation results are provided, demonstrating that our proposed scheme can achieve good performances for sensing both single and multiple dynamic paths, without requiring the presence of a LOS path.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	http://purl.org/au-research/grants/arc/DP210101411
dc.relation.ispartof	IEEE Transactions on Signal Processing
dc.relation.isbasedon	10.1109/TSP.2023.3294626
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Networking & Telecommunications
dc.title	Uplink Sensing Using CSI Ratio in Perceptive Mobile Networks
dc.type	Journal Article
utslib.citation.volume	71
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/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-27T02:36:53Z
pubs.publication-status	Published
pubs.volume	71

Abstract:

Uplink sensing in perceptive mobile networks (PMNs), which uses uplink communication signals for sensing the environment around a base station, faces challenging issues of clock asynchronism and the requirement of a line-of-sight (LOS) path between transmitters and receivers. The channel state information (CSI) ratio has been applied to resolve these issues, however, current research on the CSI ratio is limited to Doppler estimation in a single dynamic path. This paper proposes an advanced parameter estimation scheme that can extract multiple dynamic parameters, including Doppler frequency, angle-of-arrival (AoA), and delay, in a communication uplink channel and completes the localization of multiple moving targets. Our scheme is based on the multi-element complex Taylor series of the CSI ratio that converts a nonlinear function of sensing parameters to linear forms and enables the applications of traditional sensing algorithms. Using the truncated Taylor series, we develop novel multiple-signal-classification grid searching algorithms for estimating Doppler frequencies and AoAs and use the least-square method to obtain delays. Both experimental and simulation results are provided, demonstrating that our proposed scheme can achieve good performances for sensing both single and multiple dynamic paths, without requiring the presence of a LOS path.

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http://hdl.handle.net/10453/177239