Self-organizing maps
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Radio Resource Management for Wireless Networks
Radio Resource Management for Wireless Networks
Wireless Network Evolution: 2G to 3G
Wireless Network Evolution: 2G to 3G
Radio Network Planning and Optimisation for Umts
Radio Network Planning and Optimisation for Umts
Neural Analysis of Mobile Radio Access Network
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
A SOM based approach for visualization of GSM network performance data
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Advanced analysis methods for 3G cellular networks
IEEE Transactions on Wireless Communications
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
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A neural network based clustering method for the analysis of soft handovers in 3G network is introduced. The method is highly visual and it could be utilized in explorative analysis of mobile networks. In this paper, the method is used to find groups of similar mobile cell pairs in the sense of handover measurements. The groups or clusters found by the method are characterized by the rate of successful handovers as well as the causes of failing handover attempts. The most interesting clusters are those which represent certain type of problems in handover attempts. By comparing variable histograms of a selected cluster to histograms of the whole data set an application domain expert may find some explanations on problems. Two clusters are investigated further and causes of failing handover attempts are discussed.