Analyzing a 5G Dataset and Modeling Metrics of Interest

Fidan Mehmeti, Thomas F.La Porta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

The level of deployment of 5G networks is increasing every day, making this cellular technology become ubiquitous soon. Therefore, characterizing the channel quality and signal characteristics of 5G networks is of paramount importance as a first step in understanding the achievable performance of cellular users. Then, it can also serve for other important processes, such as resource planning and admission control. In this paper, we use the results of a publicly available measurement campaign of 5G users conducted by a third party and analyze various figures of merit. The analysis shows that the downlink and uplink rates for static and mobile users can be captured either by a lognormal or a Generalized Pareto distribution. Also, the time spent in the same cell by a mobile (driving) user can be captured to the best extent by a Generalized Pareto distribution. We also show some potential practical applications, among which is the prediction of the number of active users in the cell.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-88
Number of pages8
ISBN (Electronic)9781665406680
DOIs
StatePublished - 2021
Event17th International Conference on Mobility, Sensing and Networking, MSN 2021 - Virtual, Exeter, United Kingdom
Duration: Dec 13 2021Dec 15 2021

Publication series

NameProceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021

Conference

Conference17th International Conference on Mobility, Sensing and Networking, MSN 2021
Country/TerritoryUnited Kingdom
CityVirtual, Exeter
Period12/13/2112/15/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management

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