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Positioning in 5G and 6G Networks—A Survey

Mogyorósi, Ferenc and Revisnyei, Péter and Pašić, Azra and Papp, Zsófia and Törös, István and Varga, Pál and Pašić, Alija (2022) Positioning in 5G and 6G Networks—A Survey. SENSORS, 22 (13). ISSN 1424-8220

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: positioning techniques; machine learning; 5G; 6G; network-based positioning; indoor positioning; asset tracking; positioning use cases
Subjects: T Technology / alkalmazott, műszaki tudományok > T2 Technology (General) / műszaki tudományok általában
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 26 Sep 2022 09:33
Last Modified: 26 Sep 2022 09:33
URI: http://real.mtak.hu/id/eprint/149721

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