Mobile Cellular Network-Based Positioning Using Machine Learning

Authors

  • Reda Yagoub University of Ain Témouchent
  • Samia Bentaieb University of Ain Témouchent
  • Roumaissa Anberi University of Ain Témouchent
  • Fouzia Bakhti University of Ain Témouchent

Abstract

Positioning systems are essential for various applications, ranging from navigation to location-based services. In the case of mobile cellular networks. This study explored the use of mobile cellular network signals to develop a positioning system for beehives. Our research introduces a new approach for positioning using mobile cellular (LTE, UMTS, and GSM) radio signal data. We trained a machine learning model to predict geographic coordinates (latitude and longitude) based on various parameters extracted from the intercepted radio signals. These parameters include the Cell Identity, Mobile Country Code (MCC), Mobile Network Code (MNC), Location Area Code (LAC), and additional relevant identifiers.Our study offers a novel approach for precise position determination by utilizing information provided by mobile cellular signals.

Additional Files

Published

2026-05-16

Issue

Section

Telecommunications