A SOM based approach for visualization of GSM network performance data

In this paper, a neural network based approach to visualize performance data of a GSM network is presented. The proposed approach consists of several steps. First, a suitable proportion of measurement data is selected. Then, the selected set of multi-dimensional data is projected into two-dimensional space for visualization purposes with a neural network algorithm called Self-Organizing Map (SOM). Then, the data is clustered and additional visualizations for each data cluster axe provided in order to infer the presence of various failure types, their sources and times of occurrence. We apply the proposed approach in the analysis of degradations in signaling and traffic channel capacity of a GSM network.