Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Train Velocity and Data Throughput - A Large Scale LTE Cellular Measurements Study
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed systems and communication (DISCO))
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed systems and communication (DISCO))ORCID iD: 0000-0003-0368-9221
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed systems and communication (DISCO))ORCID iD: 0000-0001-7311-9334
KTH, Center for Wireless Systems.
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Train-mounted aggregation routers that provide WiFi access to train passengers and bundle external communication over multiple cellular modems/links is an efficient way of providing communication services on trains. However, the characteristics of such systems have received limited attention in the literature. In this paper we address this gap by examining the communication characteristics of such systems based on a large data set gathered over six months from an operational Swedish railway system. We focus our examination on the relationship between per link throughput and train velocity. Using Levenberg- Marquardt non-linear regression a noticeable critical point is observed for an RS-SINR of around 12 dB. At this point the impact of increased train velocity on per link throughput changes from being negative to becoming positive. Using a machine learning approach we also explore the relative importance of several observed metrics in relation to per link throughput.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Cellular networks, LTE, 4G, Trains
National Category
Computer Science Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65251OAI: oai:DiVA.org:kau-65251DiVA: diva2:1159472
Conference
IEEE 86th Vehicular Technology Conference Fall 2017. 24 – 27 September 2017 Toronto, Canada.
Projects
HITS
Available from: 2017-11-22 Created: 2017-11-22 Last updated: 2017-11-22

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Johan, GarciaAlfredsson, StefanBrunström, Anna
By organisation
Department of Mathematics and Computer Science
Computer ScienceTelecommunications

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 18 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf