Deep Learning-Based Autoencoder for m-User Wireless Interference Channel Physical Layer Design

Deep Learning-Based Autoencoder for m-User Wireless Interference Channel Physical Layer Design

Deep learning (DL) based autoencoder (AE) has been proposed recently as a promising, and potentially disruptive approach to design the physical layer of beyond-5G communication systems. Compared to a traditional communication system with a multiple-block structure, the DL based AE approach provides...

Full description

Bibliographic Details
Main Authors: Dehao Wu, Maziar Nekovee, Yue Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep learning
autoencoder
5G physical layer
interference channel
Online Access:https://ieeexplore.ieee.org/document/9204706/

Internet

https://ieeexplore.ieee.org/document/9204706/

Similar Items