Abstract:
In this article, we introduce a statistics-based clustering framework that is able to model the clustering problem corresponding to the channel propagation characteristic...View moreMetadata
Abstract:
In this article, we introduce a statistics-based clustering framework that is able to model the clustering problem corresponding to the channel propagation characteristics and evaluate the clustering results effectively. In the framework a Gaussian mixture model (GMM) is employed to model the channel multipaths. Then, we optimize the GMM parameters with the expectation-maximization (EM) algorithm. To evaluate the clustering results effectively, a compact index (CI) is devised, in which both the mean and variance of the clusters are considered. In the simulation, outdoor-to-indoor (O2I) channel measurement data is presented to demonstrate the effectiveness of the proposed framework.
Date of Conference: 15-18 April 2018
Date Added to IEEE Xplore: 11 June 2018
ISBN Information:
Electronic ISSN: 1558-2612