Deep Learning in Physical Layer Communications.

IEEE Wireless Communications(2019)

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摘要
DL has shown great potential to revolutionize communication systems. This article provides an overview of 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 the block structure, we demonstrate the power of DL in signal compression and signal detection. We also discuss the recent endeavors in developing DL-based end-to-end communication systems. Finally, potential research directions are identified to boost intelligent physical layer communications. Introduction
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关键词
Communication systems,Neurons,Gallium nitride,Physical layer,Mathematical model,Training,Biological neural networks
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