Development of an Uplink Sensing Demonstrator for Perceptive Mobile Networks

Chen, K; Zhang, JA; Wang, Z; Guo, YJ

Development of an Uplink Sensing Demonstrator for Perceptive Mobile Networks

Chen, K Zhang, JA Wang, Z

Guo, YJ

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 22nd International Symposium on Communications and Information Technologies (ISCIT), 2024, 00, pp. 191-196
Issue Date:: 2024-01-03

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Field	Value	Language
dc.contributor.author	Chen, K
dc.contributor.author	Zhang, JA
dc.contributor.author	Wang, Z https://orcid.org/0000-0003-3611-9540
dc.contributor.author	Guo, YJ
dc.date	2023-10-16
dc.date.accessioned	2025-03-14T03:28:45Z
dc.date.available	2025-03-14T03:28:45Z
dc.date.issued	2024-01-03
dc.identifier.citation	2023 22nd International Symposium on Communications and Information Technologies (ISCIT), 2024, 00, pp. 191-196
dc.identifier.isbn	978-1-6654-5731-6
dc.identifier.issn	2643-6140
dc.identifier.issn	2643-6175
dc.identifier.uri	http://hdl.handle.net/10453/185807
dc.description.abstract	Uplink sensing offers a cost effective solution to real time detection and tracking of moving objects in Perceptive Mobile Networks PMN which integrates sensing into mobile networks Currently there has been extensive research on passive human localization techniques based on millimeter wave radar and Wi Fi whereas there are relatively few reports on passive human localization using mobile networks This paper introduces the development of a real time uplink sensing demonstrator for PMN enabling sub meter precision tracking in indoor environments Motion related parameters such as Doppler frequency angle of arrival AoA and dynamic propagation delay are estimated instantly within a sampling window of around 200 milliseconds This prototype system achieves the median localization precision of 76 cm and the 80 localization precision of 107 cm in an office setting
dc.language	en
dc.publisher	IEEE
dc.relation	http://purl.org/au-research/grants/arc/DP210101411
dc.relation.ispartof	2023 22nd International Symposium on Communications and Information Technologies (ISCIT)
dc.relation.ispartof	International Symposium on Communications and Information Technologies
dc.relation.isbasedon	10.1109/iscit57293.2023.10376089
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Development of an Uplink Sensing Demonstrator for Perceptive Mobile Networks
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Sydney, Australia
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	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2025-03-14T03:28:43Z
pubs.finish-date	2023-10-18
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2023-10-16
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

Uplink sensing offers a cost effective solution to real time detection and tracking of moving objects in Perceptive Mobile Networks PMN which integrates sensing into mobile networks Currently there has been extensive research on passive human localization techniques based on millimeter wave radar and Wi Fi whereas there are relatively few reports on passive human localization using mobile networks This paper introduces the development of a real time uplink sensing demonstrator for PMN enabling sub meter precision tracking in indoor environments Motion related parameters such as Doppler frequency angle of arrival AoA and dynamic propagation delay are estimated instantly within a sampling window of around 200 milliseconds This prototype system achieves the median localization precision of 76 cm and the 80 localization precision of 107 cm in an office setting

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http://hdl.handle.net/10453/185807