Deep Learning in Physical Layer Communications
Queen Mary University of London · Georgia Institute of Technology
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
- FWCI
- 61.56
- Percentile
- 100%
- References
- 18
Authors
4Topics & keywords
- Physical layer
- Computer science
- Communications system
- Transmitter
- Block (permutation group theory)
- Layer (electronics)
- Categorization
- Telecommunications