Positioning in 5G and 6G Networks-A Survey

Sensors (Basel). 2022 Jun 23;22(13):4757. doi: 10.3390/s22134757.

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.

Keywords: 5G; 6G; asset tracking; indoor positioning; machine learning; network-based positioning; positioning techniques; positioning use cases.

Publication types

  • Review

MeSH terms

  • Algorithms*
  • Geographic Information Systems*
  • Humans
  • Surveys and Questionnaires

Grant support

The research leading to these results was supported by Ericsson and the High Speed Networks Laboratory (HSNLab). Project no. 137698 has been implemented with the support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the PD_21 funding scheme. This paper was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.