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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

M. Rindler, S. Caban, M. Lerch, P. Svoboda, M. Rupp:
"Swift Indoor Benchmarking Methodology for Mobile Broadband Networks";
Vortrag: IEEE 86th Vehicular Technology Conference (VTC2017-Fall), Toronto; 24.09.2017 - 27.09.2017; in: "IEEE 86th Vehicular Technology Conference (VTC2017-Fall)", (2017).



Kurzfassung englisch:
In an operational cellular mobile network, measuring the mean mobile broadband performance at a certain place in a building within a short time (e.g., several minutes) is a challenging task as fading is position dependent and the overall network load changes throughout a day.
In this work we derive a measurement methodology that allows for swift and repeatable measurements of the mean network performance by combining three techniques: Firstly, the instantaneous IP-throughput is derived within one second by using a novel packet pattern method on an Android cell phone with external antennas. Secondly, the long-term trend in the IP performance, that is the slowly changing average network load, is removed. Thirdly, the scenario mean of the remaining small scale fading scenario with overlaid fast network fluctuations is obtained by statistical inference, namely, spatial systematic sampling with an XY-positioning table. To assess the validity of our approach we present the results of a seven day long measurement campaign in a live 4G network in Vienna, Austria. We show that, once the long-term network trend's influcence is removed, a measurement run over twenty seconds is sufficient to determine the weekly mean IP-throughput performance at an indoor location with an error of 10% at 90% level of confidence.

Schlagworte:
Benchmarking, Mobile Network, indoor, MBB, Performance


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/VTCFall.2017.8288190

Elektronische Version der Publikation:
http://publik.tuwien.ac.at/files/publik_261883.pdf


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.