Analysis of the expansion of a GSM network using Gaussian Processes
DOI:
https://doi.org/10.15332/iteckne.v10i2.391Keywords:
Gaussian Processes, GSM networks, KPIs, machine learning, regression.Abstract
Abstract— the expansion plan of a Global System Mobile (GSM) network requires the analysis of some important variables known as key performance indicators (KPI) on the network. Network operators have tools for analyzing a KPI behavior on a particular network cell. This paper proposes a tool that illustrates graphically the behavior-in-time of a KPI in a whole geographical zone (including cell positions). A Gaussian process repressor is used over a real data set and time-space inference is performed. Finally we observe how a particular region presents high-KPI values most of the time. This alerts the network operator for including a solution in the formulation phase of the network expansion plan.
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