Bo Bernhardsson
Modellering och styrning av osäkra system. Programdirektör för masterprogrammet i maskininlärning, system och styrning.
ML-Enabled Outdoor User Positioning in 5G NR Systems via Uplink SRS Channel Estimates
Författare
Redaktör
- Michele Zorzi
- Meixia Tao
- Walid Saad
Summary, in English
Cellular user positioning is a promising service provided by Fifth Generation New Radio (5G NR) networks. Besides, Machine Learning (ML) techniques are foreseen to become an integrated part of 5G NR systems improving radio performance and reducing complexity. In this paper, we investigate ML techniques for positioning using 5G NR fingerprints consisting of uplink channel estimates from the physical layer channel. We show that it is possible to use Sounding Reference Signals (SRS) channel fingerprints to provide sufficient data to infer user position. Furthermore, we show that small fully-connected moderately Deep Neural Networks, even when applied to very sparse SRS data, can achieve successful outdoor user positioning with meter-level accuracy in a commercial 5G environment.
Avdelning/ar
- MAX IV-laboratoriet
- LTH profilområde: AI och digitalisering
- Kommunikationsteknologi
- LU profilområde: Naturlig och artificiell kognition
- LTH profilområde: Teknik för hälsa
- Institutionen för reglerteknik
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication
Publiceringsår
2023
Språk
Engelska
Sidor
2215-2220
Publikation/Tidskrift/Serie
IEEE International Conference on Communications
Volym
2023-May
Länkar
Dokumenttyp
Konferensbidrag
Förlag
IEEE - Institute of Electrical and Electronics Engineers Inc.
Ämne
- Telecommunications
Nyckelord
- 5G
- beamforming
- deep neural network
- localization
- machine learning
- positioning
- radio access network
- sounding reference signal
Conference name
2023 IEEE International Conference on Communications, ICC 2023
Conference date
2023-05-28 - 2023-06-01
Conference place
Rome, Italy
Status
Published
Forskningsgrupp
- Communications Engineering
ISBN/ISSN/Övrigt
- ISSN: 1550-3607
- ISBN: 9781538674628