Multi-Operator Cell Tower Locations Prediction from Crowdsourced Data
Document Type
Conference Proceeding
Publication Date
7-1-2021
Abstract
Cell tower locations are not publicly available due to business interests of wireless providers. Very often wireless providers provide exaggerated coverage maps that may mislead the public. In addition to providing a neutral check on the coverage maps, prediction of cell tower locations hosting multiple operators' access nodes could also be helpful in disaster communications and public safety in general. The localization of the disaster-Affected towers can be very conducive to respond and reach to the victims. Further, victims' devices could utilize this knowledge to initiate device-To-device (D2D) or unmanned aerial vehicular (UAV) communications as alternatives to the damaged cellular infrastructure. Publicly available crowdsourced cell (base station) locations and FCC's sites can be used to predict the cell tower/site locations in the United States. In this work, we utilized a weighted k-means algorithm to predict cell tower locations from OpenCellid crowdsourced dataset and implemented a mapping algorithm to locate nearest physical towers. We map the predicted towers to two different sources of physical towers. Our comparison shows a significant accuracy in predicting tower locations regardless of sources of physical towers. The technique can be used to predict the tower locations in other countries as well.
Identifier
85114962723 (Scopus)
ISBN
[9780738113302]
Publication Title
Proceedings International Conference on Computer Communications and Networks ICCCN
External Full Text Location
https://doi.org/10.1109/ICCCN52240.2021.9522192
ISSN
10952055
Volume
2021-July
Grant
16226110
Fund Ref
National Science Foundation
Recommended Citation
Rahman, Mostafizur; Hossain, Mohammad Arif; and Yuksel, Murat, "Multi-Operator Cell Tower Locations Prediction from Crowdsourced Data" (2021). Faculty Publications. 4005.
https://digitalcommons.njit.edu/fac_pubs/4005