A Machine Learning-Based Technique for the Classification of Indoor/Outdoor Cellular Network Clients

Abstract

In this paper, we propose a machine learning-based indoor/outdoor (IO) user classification algorithm in cellular systems as pertains to 3G networks. We consider different scenarios. The experimental results show that the best machine learning algorithm for IO classification is the boosting algorithm with an accuracy that reaches 88.9%.