  Deep learning (DL) has shown the great potentials to break the bottleneck of
communication systems. This article provides an overview on the recent
advancements in DL-based physical layer communications. DL can improve the
performance of each individual block in communication systems or optimize the
whole transmitter/receiver. Therefore, we categorize the applications of DL in
physical layer communications into systems with and without block structures.
For DL-based communication systems with block structures, we demonstrate the
power of DL in signal compression and signal detection. We also discuss the
recent endeavors in developing end-to-end communication systems. Finally, the
potential research directions are identified to boost the intelligent physical
layer communications with DL.
