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This work introduces a novel wireless MIMO channel clustering technique implemented in angular and delay domains. The clustering is preceded by extraction of angular and delay information from the sampled impulse response. Akaike information criterion (AIC) has been used to find the number of multipath components arriving at the same delay bin but having different directions of incidence. The latter have been resolved with ESPRIT algorithm. A modified Saleh-Valenzuela model is used as a basis for the derivation of the unsupervised clustering algorithm. To avoid estimation of the joint angle-delay density function required for the clustering algorithm, it is 'factorized' algorithmically by first identifying clusters in the delay domain and then finding angular clusters 'conditioned' on the corresponding delay cluster. The algorithm has been applied to measured MIMO channel impulse responses and is able to find visually identifiable clusters as well as their width.