Bayesian Diagnosis and Reliability Analysis of Private Mobile Radio Networks

In this paper we discuss the use of Bayesian network graphs for network modeling and resiliency estimation problems related to Private Mobile Radio (PMR) networks. We specifically focus on network availability computation and fault diagnosis, when measurement data of only a part of the system is available to infer the state of the rest of the network. The resiliency of such uncertain networks strongly depends on the adopted redundancy mechanism. Based on bayesian graph and probability propagation techniques, we model and evaluate PMR system availability using different redundancy schemes. Our results show that the bayesian network model we propose provides accurate and straightforward estimations on system reliability and fault diagnosis.