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- Title:
PEACH: Proactive and Environment Aware Channel State Information Prediction with Depth Images - Dataset
- 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
- 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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