id:"swepub:oai:DiVA.org:kau-91608"
Search: id:"swepub:oai:DiVA.org:kau-91608" > Positioning by fing...
- 1 of 1
- Previous record
- Next record
- To hitlist
Positioning by fingerprinting with multiple cells in NB-IoT networks
-
- De Nardis, Luca (author)
- Sapienza Univ Rome, Italy
-
- Caso, Giuseppe (author)
- Ericsson Res, Kista, Sweden
-
- Alay, Ozgu (author)
- Univ Oslo, Norway
- show more...
- show less...
- (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2022
- 2022
- English.
- Conference paper (peer-reviewed)
Abstract
Subject headings
Close
- Narrowband Internet of Things (NB-IoT) has quickly become a leading technology in the deployment of IoT systems and services, thanks to its appealing features in terms of coverage and energy efficiency, as well as compatibility with existing mobile networks. Increasingly, IoT services and applications require location information to be paired with data collected by devices; NB-IoT still lacks, however, reliable positioning methods. Time-based techniques inherited from Long Term Evolution (LTE) are not yet widely available in existing networks, and are expected to perform poorly on NB-IoT signals due to their narrow bandwidth. This investigation proposes a set of strategies for NB-IoT positioning, based on fingerprinting, that use coverage and radio information from multiple cells. The proposed strategies are evaluated on a large-scale dataset that includes experimental data from two NB-IoT operators. Results show that the proposed strategies, using a combination of coverage and radio information from multiple cells, outperform current state-of-the-art approaches based on single cell finger-printing, with a minimum average positioning error of about 20 meters, consistent across different network scenarios, vs. about 70 meters for current state-of-the-art.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Energisystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Energy Systems (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Arbetsmedicin och miljömedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Occupational Health and Environmental Health (hsv//eng)
- NATURVETENSKAP -- Fysik -- Den kondenserade materiens fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences -- Condensed Matter Physics (hsv//eng)
Keyword
- Cells; Cytology; Energy efficiency; Large dataset; Long Term Evolution (LTE)
- ’current; Fingerprinting; Leading technology; Location information; Multiple cells; Narrow bands; Narrowband internet of thing; Positioning; Positioning methods; Services and applications
- Internet of things
Publication and Content Type
- ref (subject category)
- kon (subject category)
To the university's database
- 1 of 1
- Previous record
- Next record
- To hitlist
Find more in SwePub
- By the author/editor
- De Nardis, Luca
- Caso, Giuseppe
- Alay, Ozgu
- Ali, Usman
- Neri, Marco
- Brunström, Anna, ...
- show more...
- Di Benedetto, Ma ...
- show less...
- About the subject
-
- ENGINEERING AND TECHNOLOGY
- ENGINEERING AND ...
- and Environmental En ...
- and Energy Systems
-
- MEDICAL AND HEALTH SCIENCES
- MEDICAL AND HEAL ...
- and Health Sciences
- and Occupational Hea ...
-
- NATURAL SCIENCES
- NATURAL SCIENCES
- and Physical Science ...
- and Condensed Matter ...
- By the university
- Karlstad University
Search outside SwePub
- Extend your search to:
- Google Book Search
- Google Scholar
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.
- Copyright © LIBRIS - National Library Systems
- LIBRIS.kb.se
