Deep learning has a wide application in the area of natural language processing and image
processing due to its strong ability of generalization. In this paper, we propose a novel …

Deep learning has been applied in physical-layer communications systems in recent years
and has demonstrated fascinating results that were comparable or even better than human …

Historically, most of the channel encoding and decoding algorithms have been designed to
deal with and evaluated under the additive white Gaussian noise (AWGN) channel …

With the development of 5G, the future wireless communication network tends to be more
and more intelligent. In the face of new service demands of communication in the future such …

Recent research in the design of end to end communication system using deep learning has
produced models which can outperform traditional communication schemes. Most of these …

In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large
antenna arrays to achieve high gain and spectral efficiency. These massive MIMO systems …

This paper demonstrates exceptional performance of approximately 10.0 dB learning-based
gain using the Deep Convolutional Neural Network (DCNN) for demodulation of a Rayleigh …

The 5G and beyond wireless networks will be more dynamic and heterogeneous, which
needs to work on multistrand waveforms. One of the most significant challenges in such a …

We present and discuss several novel applications of deep learning for the physical layer.
By interpreting a communications system as an autoencoder, we develop a fundamental …

Machine learning (ML) has been widely applied to the upper layers of wireless
communication systems for various purposes, such as deployment of cognitive radio and …