SwePub
Sök i LIBRIS databas

  Utökad sökning

id:"swepub:oai:DiVA.org:kau-91608"
 

Sökning: id:"swepub:oai:DiVA.org:kau-91608" > Positioning by fing...

Positioning by fingerprinting with multiple cells in NB-IoT networks

De Nardis, Luca (författare)
Sapienza Univ Rome, Italy
Caso, Giuseppe (författare)
Ericsson Res, Kista, Sweden
Alay, Ozgu (författare)
Univ Oslo, Norway
visa fler...
Ali, Usman (författare)
Sapienza Univ Rome, Italy
Neri, Marco (författare)
Rohde&Schwarz, Italy
Brunström, Anna, 1967- (författare)
Karlstads universitet,Centrum för HumanIT,Institutionen för matematik och datavetenskap (from 2013)
Di Benedetto, Maria-Gabriella (författare)
Sapienza Univ Rome, Italy
visa färre...
 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
Engelska.
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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. 

Ämnesord

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)

Nyckelord

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

Publikations- och innehållstyp

ref (ämneskategori)
kon (ämneskategori)

Till lärosätets databas

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.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy