Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks

Jukka Talvitie; Toni Levanen; Mike Koivisto; Tero Ihalainen; Kari Pajukoski; Markku Renfors; Mikko Valkama

doi:10.1109/GLOCOMW.2018.8644311

Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks

Jukka Talvitie
, Toni Levanen
, Mike Koivisto
, Tero Ihalainen
, Kari Pajukoski
, Markku Renfors
, Mikko Valkama

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

35 Citations (Scopus)

264 Downloads (Pure)

Abstract

High-accuracy positioning enables emerging of new vertical markets for the forthcoming fifth generation (5G) mobile networks. In this paper, we study network-side positioning and related location-based beamforming for high-speed train (HST) scenario in 5G New Radio (NR) networks. To avoid tight synchronization requirements between the train and the network, we consider Time-Difference-Of-Arrival (TDOA) measurements based on 5G NR uplink sounding reference signals. Moreover, in order to facilitate the location-based beamforming, we introduce methods for removing measurement outliers and for selecting the optimal reference measurement for the time-difference evaluations. The train is tracked by utilizing Extended Kalman Filter (EKF), which is capable to track and predict the train position for the location-based beamformer in real-time. Based on results obtained from extensive 5G NR compliant simulations, the proposed approach is able to achieve a sub-meter positioning accuracy with 90% availability, which is sufficient for many mission-critical positioning applications in the considered HST scenario.

Original language	English
Title of host publication	2018 IEEE Globecom Workshops (GC Wkshps)
Subtitle of host publication	7th International Workshop on Emerging Technologies for 5G and Beyond Wireless and Mobile Networks (ET5GB)
Publisher	IEEE
Number of pages	7
ISBN (Electronic)	978-1-5386-4920-6
ISBN (Print)	978-1-5386-4921-3
DOIs	https://doi.org/10.1109/GLOCOMW.2018.8644311
Publication status	Published - Dec 2018
Publication type	A4 Article in conference proceedings
Event	IEEE Globecom Workshops - Duration: 1 Jan 2000 → …

Conference

Conference	IEEE Globecom Workshops
Period	1/01/00 → …

Publication forum classification

Publication forum level 1

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10.1109/GLOCOMW.2018.8644311

Positioning and Location-based Beamforming 2018
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Accepted author manuscript, 382 KB

http://urn.fi/URN:NBN:fi:tuni-202002051856

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Talvitie, J., Levanen, T., Koivisto, M., Ihalainen, T., Pajukoski, K., Renfors, M., & Valkama, M. (2018). Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks. In 2018 IEEE Globecom Workshops (GC Wkshps): 7th International Workshop on Emerging Technologies for 5G and Beyond Wireless and Mobile Networks (ET5GB) IEEE. https://doi.org/10.1109/GLOCOMW.2018.8644311

@inproceedings{31f1547ec7e34616b01969403e6e03cd,

title = "Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks",

abstract = "High-accuracy positioning enables emerging of new vertical markets for the forthcoming fifth generation (5G) mobile networks. In this paper, we study network-side positioning and related location-based beamforming for high-speed train (HST) scenario in 5G New Radio (NR) networks. To avoid tight synchronization requirements between the train and the network, we consider Time-Difference-Of-Arrival (TDOA) measurements based on 5G NR uplink sounding reference signals. Moreover, in order to facilitate the location-based beamforming, we introduce methods for removing measurement outliers and for selecting the optimal reference measurement for the time-difference evaluations. The train is tracked by utilizing Extended Kalman Filter (EKF), which is capable to track and predict the train position for the location-based beamformer in real-time. Based on results obtained from extensive 5G NR compliant simulations, the proposed approach is able to achieve a sub-meter positioning accuracy with 90\% availability, which is sufficient for many mission-critical positioning applications in the considered HST scenario.",

author = "Jukka Talvitie and Toni Levanen and Mike Koivisto and Tero Ihalainen and Kari Pajukoski and Markku Renfors and Mikko Valkama",

year = "2018",

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language = "English",

isbn = "978-1-5386-4921-3",

booktitle = "2018 IEEE Globecom Workshops (GC Wkshps)",

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Talvitie, J, Levanen, T, Koivisto, M, Ihalainen, T, Pajukoski, K, Renfors, M & Valkama, M 2018, Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks. in 2018 IEEE Globecom Workshops (GC Wkshps): 7th International Workshop on Emerging Technologies for 5G and Beyond Wireless and Mobile Networks (ET5GB). IEEE, IEEE Globecom Workshops, 1/01/00. https://doi.org/10.1109/GLOCOMW.2018.8644311

Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks. / Talvitie, Jukka; Levanen, Toni; Koivisto, Mike et al.
2018 IEEE Globecom Workshops (GC Wkshps): 7th International Workshop on Emerging Technologies for 5G and Beyond Wireless and Mobile Networks (ET5GB). IEEE, 2018.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks

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AU - Levanen, Toni

AU - Koivisto, Mike

AU - Ihalainen, Tero

AU - Pajukoski, Kari

AU - Renfors, Markku

AU - Valkama, Mikko

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N2 - High-accuracy positioning enables emerging of new vertical markets for the forthcoming fifth generation (5G) mobile networks. In this paper, we study network-side positioning and related location-based beamforming for high-speed train (HST) scenario in 5G New Radio (NR) networks. To avoid tight synchronization requirements between the train and the network, we consider Time-Difference-Of-Arrival (TDOA) measurements based on 5G NR uplink sounding reference signals. Moreover, in order to facilitate the location-based beamforming, we introduce methods for removing measurement outliers and for selecting the optimal reference measurement for the time-difference evaluations. The train is tracked by utilizing Extended Kalman Filter (EKF), which is capable to track and predict the train position for the location-based beamformer in real-time. Based on results obtained from extensive 5G NR compliant simulations, the proposed approach is able to achieve a sub-meter positioning accuracy with 90% availability, which is sufficient for many mission-critical positioning applications in the considered HST scenario.

AB - High-accuracy positioning enables emerging of new vertical markets for the forthcoming fifth generation (5G) mobile networks. In this paper, we study network-side positioning and related location-based beamforming for high-speed train (HST) scenario in 5G New Radio (NR) networks. To avoid tight synchronization requirements between the train and the network, we consider Time-Difference-Of-Arrival (TDOA) measurements based on 5G NR uplink sounding reference signals. Moreover, in order to facilitate the location-based beamforming, we introduce methods for removing measurement outliers and for selecting the optimal reference measurement for the time-difference evaluations. The train is tracked by utilizing Extended Kalman Filter (EKF), which is capable to track and predict the train position for the location-based beamformer in real-time. Based on results obtained from extensive 5G NR compliant simulations, the proposed approach is able to achieve a sub-meter positioning accuracy with 90% availability, which is sufficient for many mission-critical positioning applications in the considered HST scenario.

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DO - 10.1109/GLOCOMW.2018.8644311

M3 - Conference contribution

SN - 978-1-5386-4921-3

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PB - IEEE

T2 - IEEE Globecom Workshops

Y2 - 1 January 2000

ER -

Positioning and Location-based Beamforming for High Speed Trains in 5G NR Networks

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