In this letter, we propose a Gaussian mixture model (GMM)-based channel estimator which is learned on imperfect training data, i.e., the training data are solely comprised of noisy and sparsely ...

We encode the data with a Gaussian Mixture Model in the parameter space of probabilistic movement primitives, after performing dimensionality reduction on such parameter space. We append the ...