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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

V. Raida, P. Svoboda, M. Rupp:
"Modified Dynamic Time Warping with a Reference Path for Alignment of Repeated Drive-Tests";
Vortrag: Online Conference 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), Victoria, Canada; 18.11.2020; in: "IEEE 92nd Vehicular Technology Conference (VTC2020-Fall)", IEEE (Hrg.); (2020), 6 S.



Kurzfassung englisch:
To provide reliable estimates of wireless network performance along a specific route, repeated measurements should always be conducted to determine the consistency and stability of the relevant key parameter indicators. If the same speed profile cannot be guaranteed during each repetition, then the alignment of the measured signals becomes a challenging task. To tackle this problem, we introduce the concept of the reference path and propose a modified dynamic time warping algorithm. By combining both ideas, we obtain a novel RP-DTW algorithm (modified dynamic time warping with a reference path) that aligns repeated measurements optimally. To demonstrate its usefulness, we apply the algorithm to measurements of received signal power in operational LTE networks of three Austrian operators, which we collected while being onboard a train that traverses between Vienna and Gmünd. We publicly offer our measurements as an open dataset.

Schlagworte:
dynamic time warping, machine learning, reference path, repeatability, spatial, coordinates, cellular, mobile, network, measurement, LTE, 5G, signal power, RSRP, dataset


Elektronische Version der Publikation:
https://publik.tuwien.ac.at/files/publik_290760.pdf


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.