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

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 …

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 …

End-to-end learning of communications systems is a fascinating novel concept that has so
far only been validated by simulations for block-based transmissions. It allows learning of …

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

Deep learning has solved many problems that are out of reach of heuristic algorithms. It has
also been successfully applied in wireless communications, even though the current radio …

In this letter we apply deep learning tools to conduct channel estimation for an orthogonal
frequency division multiplexing (OFDM) system based on downlink pilots. To be specific, a …

Wireless communications are envisioned to bring about dramatic changes in the future, with
a variety of emerging applications, such as virtual reality, Internet of Things, and so on …

Channel estimation with received signal-to-noise ratio (SNR) feedback is promising and
effective for practical wireless multiple-input multiple-output (MIMO) systems. In this paper …

End-to-end deep learning for communication systems, ie, systems whose encoder and
decoder are learned, has attracted significant interest recently, due to its performance which …