<div class="csl-bib-body">
<div class="csl-entry">Schwarzinger, P., Fastenbauer, A., Eller, L., Svoboda, P., & Rupp, M. (2024). A Data-Based Cell Load Model for Efficient Network Simulation. In <i>2024 International Symposium ELMAR</i> (pp. 61–64). https://doi.org/10.1109/ELMAR62909.2024.10694634</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/201846
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dc.description.abstract
Campus networks are shown to be able to offer service guarantees for specific user groups. However, investigations on the user throughput of campus users are missing in literature. In order to fill this gap, an efficient cell load model is developed. For this, we verify an existing model for the number of connected users to a cell in a mobile network. We then use previously proposed cell load models, in combination with the generation of the number of connected users, to offer an computationally efficient way to generate realistic cell load values. With the cell load model, simulations are performed showing that a campus cell can increase the user throughput compared to the public network if the campus cell transmit power is sufficiently high.
en
dc.description.sponsorship
Christian Doppler Forschungsgesells
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dc.language.iso
en
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dc.subject
5G
en
dc.subject
6G
en
dc.subject
campus networks
en
dc.subject
non-public networks
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dc.subject
monitoring data
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dc.title
A Data-Based Cell Load Model for Efficient Network Simulation
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
979-8-3503-7542-8
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dc.description.startpage
61
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dc.description.endpage
64
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dc.relation.grantno
01
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
2024 International Symposium ELMAR
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tuw.peerreviewed
true
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tuw.project.title
Christian Doppler Labor für Digitale Zwillinge mit integrierter KI für nachhaltigen Funkzugang