Clustering algorithm for Cellular Radio Network Planning based on Renyi's entropy and support vector

Radio cell clustering is important to Cellular Radio Network Planning for traffic prediction in cellular network. And clustering algorithm should be qualified for arbitrary shape clustering. In this research, a novel clustering algorithm based on Renyi's entropy and support vector is proposed. Support vector clustering does the divisive clustering to generate initial small clusters for next step Renyi's entropy clustering. Experiment results showed this algorithm was qualified for arbitrary shape dataset clustering.