학술논문

Deep Learning Architectures for Modeling Communication Systems
Document Type
Conference
Source
2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) Advanced Networks and Telecommunications Systems (ANTS), 2019 IEEE International Conference on. :1-5 Dec, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
machine learning
deep learning
physical layer
autoencoder
Language
ISSN
2153-1684
Abstract
Recently, deep learning for physical layer has been modeled using autoencoders to model the entire communication system end-to-end. We extend these methods to improve the overall performance by adopting various learning strategies when multiple users try to communicate over a shared channel. We consider cooperative and non-cooperative schemes in the 2-user Gaussian interference channel. Additionally, a simple neural network architecture is provided for wireless communication systems where channel gain matrix either attenuates or, in some cases, results in fading of the message signal sent by the transmitter.