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

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