Anchor Points Assisted Uplink Sensing in Perceptive Mobile Networks

Hu, Y; Zhang, JA; Wu, K; Deng, W; Guo, YJ

Anchor Points Assisted Uplink Sensing in Perceptive Mobile Networks

Hu, Y Zhang, JA Wu, K

Deng, W Guo, YJ

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Communications, 2024, 73, (2), pp. 904-920
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Hu, Y
dc.contributor.author	Zhang, JA
dc.contributor.author	Wu, K https://orcid.org/0000-0003-1298-6404
dc.contributor.author	Deng, W
dc.contributor.author	Guo, YJ
dc.date.accessioned	2025-03-07T00:43:40Z
dc.date.available	2025-03-07T00:43:40Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Transactions on Communications, 2024, 73, (2), pp. 904-920
dc.identifier.issn	0090-6778
dc.identifier.issn	1558-0857
dc.identifier.uri	http://hdl.handle.net/10453/185552
dc.description.abstract	Uplink sensing in integrated sensing and communications (ISAC) systems, such as Perceptive Mobile Networks, is challenging due to the clock asynchronism between transmitter and receiver. Existing solutions typically require the presence of a line-of-sight path and the knowledge of the transmitter’s location. In this paper, these requirements, we propose a novel uplink sensing scheme to relieve these requirements by introducing static anchor points for the first time. The scheme consists of two efficient algorithms. The first algorithm estimates the relative timing and carrier frequency offsets, with respect to a randomly selected reference snapshot. Its estimation performance is analyzed with closed-form bias and root mean squared error derived. The estimates from the first algorithm are then used to eliminate clock offsets, enabling the construction of angle-Doppler maps. Using the maps, the second algorithm is developed to identify anchor points and then locate the transmitter and dynamic targets. The impact of the locations of the transmitter and anchor points is also analytically illustrated. Extensive simulation results are provided, demonstrating the effectiveness of the proposed sensing scheme in practical 5G communication setups and its superiority over prior art in terms of noise resilience and asymptotic performances.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Communications
dc.relation.isbasedon	10.1109/TCOMM.2024.3443729
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0804 Data Format, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
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	Anchor Points Assisted Uplink Sensing in Perceptive Mobile Networks
dc.type	Journal Article
utslib.citation.volume	73
utslib.for	0804 Data Format
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Global Big Data Technologies Centre (GBDTC)
utslib.copyright.status	open_access	*
dc.date.updated	2025-03-07T00:43:38Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	73
utslib.citation.issue	2

Abstract:

Uplink sensing in integrated sensing and communications (ISAC) systems, such as Perceptive Mobile Networks, is challenging due to the clock asynchronism between transmitter and receiver. Existing solutions typically require the presence of a line-of-sight path and the knowledge of the transmitter’s location. In this paper, these requirements, we propose a novel uplink sensing scheme to relieve these requirements by introducing static anchor points for the first time. The scheme consists of two efficient algorithms. The first algorithm estimates the relative timing and carrier frequency offsets, with respect to a randomly selected reference snapshot. Its estimation performance is analyzed with closed-form bias and root mean squared error derived. The estimates from the first algorithm are then used to eliminate clock offsets, enabling the construction of angle-Doppler maps. Using the maps, the second algorithm is developed to identify anchor points and then locate the transmitter and dynamic targets. The impact of the locations of the transmitter and anchor points is also analytically illustrated. Extensive simulation results are provided, demonstrating the effectiveness of the proposed sensing scheme in practical 5G communication setups and its superiority over prior art in terms of noise resilience and asymptotic performances.

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http://hdl.handle.net/10453/185552