{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:11:03Z","timestamp":1778256663653,"version":"3.51.4"},"reference-count":109,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T00:00:00Z","timestamp":1655942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ericsson and the High Speed Networks Laboratory (HSNLab)","award":["137698"],"award-info":[{"award-number":["137698"]}]},{"name":"National Research, Development, and Innovation Fund of Hungary","award":["137698"],"award-info":[{"award-number":["137698"]}]},{"name":"J\u00e1nos Bolyai Research Scholarship of the Hungarian Academy of Sciences","award":["137698"],"award-info":[{"award-number":["137698"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2014indoors 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.<\/jats:p>","DOI":"10.3390\/s22134757","type":"journal-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T22:43:00Z","timestamp":1656024180000},"page":"4757","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":112,"title":["Positioning in 5G and 6G Networks\u2014A Survey"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7929-5774","authenticated-orcid":false,"given":"Ferenc","family":"Mogyor\u00f3si","sequence":"first","affiliation":[{"name":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, M\u0171egyetem rkp. 3, H-1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9459-8335","authenticated-orcid":false,"given":"P\u00e9ter","family":"Revisnyei","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, M\u0171egyetem rkp. 3, H-1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7443-0458","authenticated-orcid":false,"given":"Azra","family":"Pa\u0161i\u0107","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, M\u0171egyetem rkp. 3, H-1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5901-0989","authenticated-orcid":false,"given":"Zs\u00f3fia","family":"Papp","sequence":"additional","affiliation":[{"name":"Ericsson Research, H-1117 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8480-3545","authenticated-orcid":false,"given":"Istv\u00e1n","family":"T\u00f6r\u00f6s","sequence":"additional","affiliation":[{"name":"Ericsson Research, H-1117 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8475-3610","authenticated-orcid":false,"given":"P\u00e1l","family":"Varga","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, M\u0171egyetem rkp. 3, H-1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6346-496X","authenticated-orcid":false,"given":"Alija","family":"Pa\u0161i\u0107","sequence":"additional","affiliation":[{"name":"Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, M\u0171egyetem rkp. 3, H-1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1109\/MNET.2019.1800366","article-title":"Machine-Learning-Based Positioning: A Survey and Future Directions","volume":"33","author":"Li","year":"2019","journal-title":"IEEE Netw."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lu, Y., Richter, P., and Lohan, E.S. 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