SON conflict diagnosis in heterogeneous networks

In trying to meet the demands of traffic hungry users, mobile network operators are faced with increased CAPital EXpenditures (CAPEX) and OPerational EXpenditures (OPEX). The Self Organizing Network (SON) functions have been introduced by 3GPP as a means to cut down these costs. There are mainly 3 categories of such functions: self-configuration, self-optimization and self-healing. In this paper we focus on the second which represents the SON functions performing a runtime optimization of the network. We center our attention on LTE heterogeneous networks. Having several SON functions in a network may lead to conflicts and potentially to bad network Key Performance Indicators (KPIs). Thus a troubleshooting mechanism has to be envisaged. Such a mechanism typically contains 3 steps: fault detection, cause diagnosis and solution deployment. In this paper we tackle the first two and we study the feasibility of using the Naive Bayes Classifier (NBC) in order to build a framework for SON Conflict Diagnosis (SONCD). We provide numeric results proving the feasibility of the framework.