Jakob Hoydis' (supported by Sebastian Cammerer, Sebastian Dörner and Tim Uhlemann) full lecture at the 2020 European School of Information Theory Stuttgart, Germany
Machine learning (ML) starts to be widely adopted in the telecommunications industry for the optimization and implementation of the fifth generation of cellular networks (5G). However, no component of 5G has been designed by ML. In this talk, I will describe the idea of and road towards a possible 6G system which is designed in a way that ML is given the opportunity to design parts of the physical and medium access layers itself.
The talk is augmented by a practical tutorial on Deep Learning (DL) for communications with a focus on the physical layer. The tutorial provides Tensorflow code for serveral examples as well as a live demonstration.