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About Deep Learning in Physical Layer Communications: Zhijin Qin, Hao Ye, Geoffrey Ye Li, and Biing-Hwang Fred Juang
This document provides an overview of recent advancements in applying deep learning to physical layer communications. Deep learning can improve individual blocks in communication systems or optimize the entire transmitter/receiver. Applications are categorized as systems with or without block structures. Deep learning shows promise in signal compression and detection for block-structured systems. Recent work also explores end-to-end communication systems without distinct blocks. The document identifies challenges for physical layer communications and how deep learning could help address gaps between theory and practical systems.
Detailed Information
| Author: | ['HiteshHarithas'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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