Journal ArticleDOI
System for automated diagnosis in cellular networks based on performance indicators
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TLDR
A model has been built based on data from a real network and the automated diagnosis system has been used to classify problems in a cellular network, showing that the solution is easily implemented and that the diagnosis accuracy is very high, therefore leading to a reduction in the operational costs of running the network.Abstract:
This paper presents a system for automated diagnosis of problems in a cellular network, which comprises a method and a model. The reasoning method, based on a naive Bayesian classifier, can be applied to the identification of the fault cause in GSM/GPRS, 3G or multi-systems networks. A diagnosis model for GSM/GPRS radio access networks is also described, whose elements are available in the network management systems (NMSs) of most networks. It is shown that the statistical relations among the elements, that is the quantitative part of the model, under certain assumptions, can be completely specified by means of the parameters of beta density functions. In order to support the theoretical concepts, a model has been built based on data from a real network and the automated diagnosis system has been used to classify problems in a cellular network, showing that the solution is easily implemented and that the diagnosis accuracy is very high, therefore leading to a reduction in the operational costs of running the network. Copyright © 2005 AEIT.read more
Citations
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A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks
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From 4G to 5G: Self-organized network management meets machine learning
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A Cell Outage Management Framework for Dense Heterogeneous Networks
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Proceedings ArticleDOI
Cell outage management in LTE networks
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TL;DR: This paper presents a framework for cell outage management and outlines the key components necessary to detect and compensate outages as well as to develop and evaluate the required algorithms.
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