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Document type:
Forschungsdaten
Publication date:
01.03.2023
Responsible:
Ayvasik, Serkut
Authors:
Ayvasik, Serkut; Mehmeti, Fidan; Babaians, Edwin; Kellerer, Wolfgang
Author affiliation:
TUM
Publisher:
TUM
Title:
PEACH: Proactive and Environment Aware Channel State Information Prediction with Depth Images - Dataset
Identifier:
doi:10.14459/2022mp1694552
End date of data production:
16.05.2022
Subject area:
ELT Elektrotechnik
Resource type:
Experimente und Beobachtungen / experiments and observations; Abbildungen von Objekten / image of objects
Other resource types:
Measurements of wireless raw signals in real-world indoor lab environment along with environment videos.
Data type:
Bilder / images; Programme und Anwendungen / software and applications
Other data type:
signal measurements as binary data
Description:
PEACH dataset: 5G NR raw wireless measurements along with correlated videos of an indoor lab environment. The dataset contains 30 measurement runs obtained over 5 different days and each are taking about 3-4 minutes. The raw measurements are named after the receiver UHD models "X410" and "X310" resulting in total 60 raw measurement data. The dataset contains videos of each measurement for two cameras at different angles. Synchronized timestamps of cameras and transmitters are provided for furth...     »
Method of data assessment:
Measurement of 5G wireless I/Q samples over software defined radios with related environment video
Links:
This dataset relates to the publication: https://dl.acm.org/doi/10.1145/3579450
Key words:
5G; wireless IQ data; software defined radio; indoor wireless measurement
Technical remarks:
View and download (3 TB total, 253 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1694552):
rsync rsync://m1694552@dataserv.ub.tum.de/m1694552/
Language:
en
Rights:
by, http://creativecommons.org/licenses/by/4.0
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