Abstract
Dynamic channel clustering and modeling have recently attracted much interest. Extensive channel measurements have shown that multipath components (MPCs) generally exist as clusters. Therefore, an accurate clustering algorithm is required to model the time-varying channels. However, the dynamic behaviors of MPCs have not been well considered in the existing algorithms. In this paper, we present a new metric for MPCs’ clustering in time-variant channels, which considers MPC’s evolution in time domain and clusters MPCs based on the fluctuation and multi-dimension distance of MPC’s trajectories. The performance of the new metric is verified by comparing measurements and simulations. It is found that the proposed algorithm using the new metric can well recognize the dynamic behaviors of MPCs and identify time-varying clusters accurately.
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