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NB-IoT deep-indoor measurements in an underground tunnel system
- Citation Author(s):
-
KrzysztofMalarski
Technical University of Denmark - Submitted by:
- Krzysztof Malarski
- Last updated:
- Tue, 05/17/2022 - 22:17
- DOI:
- 10.21227/xvrx-6r04
- Data Format:
- Research Article Link:
- License:
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Abstract
Underground UE statistics measurements captured on u-blox SARAN211 NB-IoT device, frequency band 20. Signal waveform captured by means of Rohde&Schwartz TSMW device. The samples were taken along ca. 1600m of level -2 underground tunnel system under Lyngby Campus of Technical University of Denmark.
The dataset constist of 2 files:
tun_meas.zip - raw measurements grouped into 9 folders (measurement intervals - corridors). Each folder contains .mat files with UE statistics and the waveform captured at the given measurement position.
nbiot_meas.csv - a dataset combining the measurements and the engineered parametres corresponding to the UE-eNB distance or tunnel properties.
Feature explanation:
d2d - 2D distance between the UE and the eNB
d3d - 3D distance between the UE and the eNB
nc - number of close corridors (corridor crossings within the threshold distance of 20 metres)
pd_2d - 2D penetration distance
pd_3d - 3D penetration distance
x_ind, y_ind, z_ind - indoor coordinates, the edgepoint of the tunnel towards the eNB
x_out, y_out, z_out - outdoor coordinates the edgepoint of the ground surface along the straight line between the UE and the eNB
d2d_wall - 2D indoor distance
d3d_wall - 3D indoor distance
phi - elevation angle
theta - bearing angle
dcorner - distance to the farthest tunnel corner
acorner - angle to the farthest tunnel corner
dwallx - distance to the farther tunnel wall in x-axis
dwally - distance to the farther tunnel wall in y-axis
dwallz - distance to the tunnel ceiling
