articleIEEE Wireless CommunicationsMar 8, 2019Closed access

Deep Learning in Physical Layer Communications

Queen Mary University of London · Georgia Institute of Technology

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Abstract

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…

Citation impact

713
total citations
FWCI
61.56
Percentile
100%
References
18
Citations per year

Authors

4

Topics & keywords

Keywords
  • Physical layer
  • Computer science
  • Communications system
  • Transmitter
  • Block (permutation group theory)
  • Layer (electronics)
  • Categorization
  • Telecommunications
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