Outdoor NB-IoT coverage and channel information data in urban environments

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.