Outdoor NB-IoT coverage and channel information data in urban environments
收藏Zenodo2023-02-24 更新2026-04-07 收录
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https://zenodo.org/record/7674299
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资源简介:
This dataset includes data for NB-IoT networks as collected in two cities: Oslo, Norway and Rome, Italy. Data were collected using the Rohde & Schwarz TSMA6 mobile network scanner. 7 measurement campaigns are provided for Oslo, and 6 for Rome. The dataset contains the following data: Raw data for each campaign, stored in two .csv files. For a generic campaign <X>, the files are: NB-IoT_coverage_C<X>.csv including a geo-tagged data entry in each row. Each entry provides information on a Narrowband Physical Cell Identifier (NPCI), with data related to the time stamp the NPCI was detected, GPS information, network (NPCI, Operator, Country Code, eNodeB-ID) and RF signal (RSSI, SINR, RSRP and RSRQ values); NB-IoT_RefSig_cir_C<X>.csv, also including a geo-tagged data entry in each row. Each entry provides information on a NPCI, with data related to the time stamp the NPCI was detected, GPS information, network (NPCI, Operator ID, Country Code, eNodeB-ID) and Channel Impulse Response (CIR) statistics, including the maximum delay. Processed data, stored in a Matlab workspace (.mat) file for each city: data are grouped in data points, identified by <Latitude, longitude> pairs. Each data point provides RF and CIR maximum delay measurements for each <NPCI, Operator ID, eNodeB-ID> unique combination detected at the coordinates of the data point. Estimated positions of eNodeBs, stored in a csv file for each city; A matlab script and a function to extract and generate processed data from the raw data for each city. In addition, in the case of the Rome data a script to interpolate missing data in the original data is provided, as well as the corresponding interpolated data in a second matlab workspace. The interpolation rationale and procedure is detailed in: L. De Nardis, G. Caso, Ö. Alay, U. Ali, M. Neri, A. Brunstrom and M.-G. Di Benedetto, "Positioning by Multicell Fingerprinting in Urban NB-IoT networks," Sensors, Volume 23, Issue 9, Article ID 4266, April 2023. Please refer to the above publication when using and citing the dataset.
提供机构:
Karlstad University; University of Oslo; Rohde&Schwarz; Sapienza University of Rome
创建时间:
2023-02-24



