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SUMMARY 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(More)
In the last years, numerous works have analyzed the statistical distribution of indoor power line channels response. A set of models based on two main approaches, bottom-up and top-down, have been proposed. This work analyzes the statistical distribution of the attenuation and the delay spread of indoor power line channels. First, results obtained from a(More)
In the near future, several radio access technologies will coexist in Beyond 3G mobile networks (B3G), and they will be eventually transformed into one seamless global communication infrastructure. Self-managing systems (i.e., those that self-configure, self-protect, self-heal, and self-optimize) are the solution to tackle the high complexity inherent to(More)
In the last years, self-organization of cellular networks is becoming a crucial aspect of network management due to the increasing complexity of the networks. Automatic fault identification, i.e. diagnosis, is the most difficult task in self-healing. In this paper, a model based on discrete bayesian networks (BNs) is proposed for diagnosis of radio access(More)
Indoor broadband power-line noise is composed of three main terms: impulsive components, narrowband interferences and background noise. Impulsive components can be classified into three groups according to their behavior with respect to the mains cycle: periodic synchronous with the mains, periodic asynchronous with the mains and aperiodic. Periodic(More)