C. Schneider, M. Ibraheam, S. Hafner, M. Kaske, M. Hein, R. Thoma
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引用次数: 19
Abstract
For the parametrization of geometry based stochastic channel models as from the IST-WINNER or COST 273/IC1004 initiatives large data analysis from channel sounding campaigns play an important role. Whereby the reliability of cluster charaterisation as a post-processing step after the high resolution multipath estimation exhibits a crucial issue. In this contribution a framework for evaluation and development of different cluster algorithms is discussed. Furthermore a novel hierarchical algorithm is introduced and compared to standard K-means and Fuzzy-C-means algorithms. Whereby the new algorithm outperforms the standard algorithms wrt. increasing number and size of clusters.
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