An Improved RBF Network for Predicting Location in Mobile Network

In mobile network, quality of service (Qos) is difficultly guaranteed for the particularity of mobile network. If the system knows, prior to the mobile subscriber movement, the exact trajectory it will follow, the Qos can be guaranteed. Thus, location prediction is the key issue to provide quality of service to mobile subscriber. In the present paper, RBF Network of Neural Network techniques were used to predict the mobile user´s next location based on his current location as well as time. The software Matlab 6.5 was used to confirm the parameters of RBF network, and to same training data, makes the detailed contrast with resilient propagation BP and BP in learning time and steps of learning. Experiment results show that predicted locations with RBF are more effective and accurate than resilient BP.