Computer Science > Information Theory
[Submitted on 31 Jul 2018 (v1), last revised 19 Feb 2019 (this version, v3)]
Title:Deep Learning in Physical Layer Communications
View PDFAbstract: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.
Submission history
From: Zhijin Qin [view email][v1] Tue, 31 Jul 2018 09:22:14 UTC (963 KB)
[v2] Mon, 24 Sep 2018 09:31:00 UTC (2,139 KB)
[v3] Tue, 19 Feb 2019 11:56:13 UTC (2,143 KB)
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