N-gram analysis for sleeping cell detection in LTE networks

Abstract

Sleeping cell detection in a wireless network means to find the cells which are not working properly due to various reasons. The research in the area has mostly focused on cell outage detection, e.g. due to hardware failures at the base station antennas or non-optimal network planning. In this paper we extend the research into a more challenging setting which is overlooked in the literature: the case where no outages occur in the network. The essence of the proposed method for detection of problematic cells is to analyze the sequences of the events reported by the mobile terminals to the serving base stations. The suggested n-gram analysis includes dimensionality reduction and classification of the data and ends up with providing a set of abnormal users, which at the end reveal the location of the problematic cell. We verify the proposed framework with simulated LTE network data and using the minimization of drive testing (MDT) functionality to gather the training and testing data sets.