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A machine leing method for predicting the evolution of a mobile communication channel based on a specific type of convolutional neural network is developed and evaluated in a simulated multipath transmission scenario. The simulation and channel estimation are de-signed to replicate real-world scenarios and common measurements supported by reference signals in mod cellular networks. The capability of the predictor meets the requirements that a deployment of the developed method in a radio resource scheduler of a base station pos-es. Possible applications of the method are discussed.