Clustering of radio channel parameters: Evaluation of a novel automatic identification algorithm

© 2016 IEEE.A Multipath Component Distance (MCD) based Automatic Clustering Identification algorithm (ACId-MCD) is introduced to group multipath components (MPCs) obtained from radio channels. Its performance is compared with the K-means MCD algorithm using cluster data simulated with four reference scenarios of the WINNER II channel model. The results indicate that K-means MCD is outperformed for all investigated scenarios. Moreover, a by-product of the algorithm is an optimal MCD threshold that is characteristic of the cluster statistical properties for a given propagation scenario. This parameter provides a stronger physical link between the MPCs distribution and the propagation scenario.