In this article, we use deep neural networks (DNNs) to develop an end-to-end wireless
communication system, in which DNNs are employed for all signal-related functionalities …

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 …

The recent development in machine learning, especially in deep neural networks (DNN),
has enabled learning-based end-to-end communication systems, where DNNs are …

The idea of end-to-end learning of communications systems through neural network (NN)-
based autoencoders has the shortcoming that it requires a differentiable channel model. We …

In modern wireless communication systems, wireless channel modeling has always been a
fundamental task in system design and performance optimization. Traditional channel …

In this paper, we study the deep learning (DL) based end-to-end transmission systems, then
we present the analysis for the underfitting and overfitting phenomena which happen during …

Channel modeling is a critical topic when considering accurately designing or evaluating the
performance of a communications system. Most prior work in designing or learning new …

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 …

Recent developments in applying deep learning techniques to train end-to-end
communication systems have shown great promise in improving the overall performance of …

When a channel model is available, learning how to communicate on fading noisy channels
can be formulated as the (unsupervised) training of an autoencoder consisting of the …