A Machine Learning Method for Prediction of Multipath Channels

Release Date:2020-03-20  Author:Julian Ahrens, Lia Ahrens, and Hans D. Schotten  Click:

A Machine Learning Method for Prediction of Multipath Channels

Julian Ahrens1, Lia Ahrens1, and Hans D. Schotten1,2
(1. German Research Center for Artificial Intelligence, Kaiserslautern 67663, Germany;
2. Technical University of Kaiserslautern, Kaiserslautern 67663, Germany)

Abstract: In this paper, a machine learning 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 designed to replicate real-world scenarios and common measurements supported by reference signals in modern 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 poses. Possible applications of the method are discussed.
Keywords: channel estimation; channel prediction; convolutional neural network; machine learning; multipath transmission


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