Dynamic User Grouping based on Location and Heading in 5G NR Systems

Dino Pjanić; Korkut Emre  Arslantürk; Xuesong Cai; Fredrik Tufvesson

Dynamic User Grouping based on Location and Heading in 5G NR Systems

Dino Pjanić, Korkut Emre Arslantürk, Xuesong Cai, Fredrik Tufvesson

Forskningsoutput: Konferensbidrag › Konferenspaper, ej i proceeding/ej förlagsutgivet › Peer review

3 Nedladdningar (Pure)

Sammanfattning

User grouping based on geographic location in the fifth generation (5G) New Radio (NR) systems has several applications that can significantly improve network performance, user experience, and service delivery. We demonstrate how Sounding Reference Signals channel fingerprints can be used for dynamic user grouping in a 5G NR commercial deployment based on outdoor positions and heading direction employing machine learning methods such as neural networks combined with clustering methods.

Originalspråk	engelska
Antal sidor	5
Status	Accepted/In press - 2024 okt. 7
Evenemang	IEEE VEhicular Technology Conference: VTC 2024: VTC2024-Fall - Washington DC, USA Varaktighet: 2024 okt. 7 → 2024 okt. 10 https://events.vtsociety.org/vtc2024-fall/

Konferens

Konferens	IEEE VEhicular Technology Conference: VTC 2024
Förkortad titel	IEEE VEhicular Technology Conference
Land/Territorium	USA
Period	2024/10/07 → 2024/10/10
Internetadress	https://events.vtsociety.org/vtc2024-fall/

Ämnesklassifikation (UKÄ)

Telekommunikation

Tillgång till dokument

Dynamic_User_grouping_based_on_Location_and_Heading_in_5G_NR_SystemLicens: CC BY-NC-ND

Citera det här

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title = "Dynamic User Grouping based on Location and Heading in 5G NR Systems",

abstract = "User grouping based on geographic location in fifth generation (5G) New Radio (NR) systems has several applications that can significantly improve network performance, user experience, and service delivery. We demonstrate how Sounding Reference Signals channel fingerprints can be used for dynamic user grouping in a 5G NR commercial deployment based on outdoor positions and heading direction employing machine learning methods such as neural networks combined with clustering methods.",

author = "Dino Pjani{\'c} and Arslant{\"u}rk, {Korkut Emre} and Xuesong Cai and Fredrik Tufvesson",

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TY - CONF

T1 - Dynamic User Grouping based on Location and Heading in 5G NR Systems

AU - Pjanić, Dino

AU - Arslantürk, Korkut Emre

AU - Cai, Xuesong

AU - Tufvesson, Fredrik

PY - 2024/10/7

Y1 - 2024/10/7

N2 - User grouping based on geographic location in fifth generation (5G) New Radio (NR) systems has several applications that can significantly improve network performance, user experience, and service delivery. We demonstrate how Sounding Reference Signals channel fingerprints can be used for dynamic user grouping in a 5G NR commercial deployment based on outdoor positions and heading direction employing machine learning methods such as neural networks combined with clustering methods.

AB - User grouping based on geographic location in fifth generation (5G) New Radio (NR) systems has several applications that can significantly improve network performance, user experience, and service delivery. We demonstrate how Sounding Reference Signals channel fingerprints can be used for dynamic user grouping in a 5G NR commercial deployment based on outdoor positions and heading direction employing machine learning methods such as neural networks combined with clustering methods.

M3 - Paper, not in proceeding

T2 - IEEE VEhicular Technology Conference: VTC 2024

Y2 - 7 October 2024 through 10 October 2024

ER -