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Positioning in 5G and 6G Networks—A Survey

1
Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary
2
Ericsson Research, H-1117 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Academic Editor: Naveen Chilamkurti
Sensors 2022, 22(13), 4757; https://doi.org/10.3390/s22134757
Received: 13 May 2022 / Revised: 19 June 2022 / Accepted: 20 June 2022 / Published: 23 June 2022
(This article belongs to the Section Communications)
Determining the position of ourselves or our assets has always been important to humans. Technology has helped us, from sextants to outdoor global positioning systems, but real-time indoor positioning has been a challenge. Among the various solutions, network-based positioning became an option with the arrival of 5G mobile networks. The new radio technologies, minimized end-to-end latency, specialized control protocols, and booming computation capacities at the network edge offered the opportunity to leverage the overall capabilities of the 5G network for positioning—indoors and outdoors. This paper provides an overview of network-based positioning, from the basics to advanced, state-of-the-art machine-learning-supported solutions. One of the main contributions is the detailed comparison of machine learning techniques used for network-based positioning. Since new requirements are already in place for 6G networks, our paper makes a leap towards positioning with 6G networks. In order to also highlight the practical side of the topic, application examples from different domains are presented with a special focus on industrial and vehicular scenarios. View Full-Text
Keywords: positioning techniques; machine learning; 5G; 6G; network-based positioning; indoor positioning; asset tracking; positioning use cases positioning techniques; machine learning; 5G; 6G; network-based positioning; indoor positioning; asset tracking; positioning use cases
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MDPI and ACS Style

Mogyorósi, F.; Revisnyei, P.; Pašić, A.; Papp, Z.; Törös, I.; Varga, P.; Pašić, A. Positioning in 5G and 6G Networks—A Survey. Sensors 2022, 22, 4757. https://doi.org/10.3390/s22134757

AMA Style

Mogyorósi F, Revisnyei P, Pašić A, Papp Z, Törös I, Varga P, Pašić A. Positioning in 5G and 6G Networks—A Survey. Sensors. 2022; 22(13):4757. https://doi.org/10.3390/s22134757

Chicago/Turabian Style

Mogyorósi, Ferenc, Péter Revisnyei, Azra Pašić, Zsófia Papp, István Törös, Pál Varga, and Alija Pašić. 2022. "Positioning in 5G and 6G Networks—A Survey" Sensors 22, no. 13: 4757. https://doi.org/10.3390/s22134757

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