An Introduction to Deep Learning for the Physical Layer

2 Feb 2017Timothy J. O'SheaJakob Hoydis

We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end reconstruction task that seeks to jointly optimize transmitter and receiver components in a single process... (read more)

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