In this paper, we design transceivers for fading channels using autoencoders and deep
neural networks (DNN). Specifically, we consider the problem of finding (n, k) block codes …

Recently, deep learning (DL) has been successfully applied in computer vision and natural
language processing. The communication physical layer based on deep learning has …

In communication systems, deep learning techniques can provide better predictions than
model-based methods when the hidden features of the problem are prone to deviating …

We consider the design of efficient neural-network based algorithms, referred to as neural
decoders, for decoding linear and non-linear block codes, such as Hamming and constant …

In modern communication systems, multiple types of error-correcting codes can be utilized
for different transmission scenarios. Therefore, the receiver should include the decoder …

The evolution of data driven optimization has been shown advantageous in many
applications. In this paper, we propose a deep learning architecture for the wireless …

Recently, deep learning has been exploited in many fields with revolutionary breakthroughs.
In the light of this, deep learning-assisted communication systems have also attracted much …

Deep learning algorithms have proven themselves powerful in different applications
because of their ability of generalization. In this paper, we introduce a deep learning …

In this article, we develop an end-to-end wireless communication system using deep neural
networks (DNNs), where DNNs are employed to perform several key functions, including …

There have been significant research activities in recent years to automate the design of
channel encoders and decoders via deep learning. Due the dimensionality challenge in …