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 …

Artificial intelligence (AI) and machine learning (ML) have shown tremendous potential in
reshaping the landscape of wireless communications and are, therefore, widely expected to …

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 …

We propose and practically demonstrate a joint detection and decoding scheme for short-
packet wireless communications in scenarios that require to first detect the presence of a …

Artificial intelligence (AI) has become a promising solution for meeting the stringent
performance requirements on wireless physical layer in sixth-generation (6G) …

In this article, we propose a symmetric encryption end-to-end communication system based
on deep convolutional generative adversarial networks to solve the security problem of …

Deep learning has been used recently to learn error-correcting encoders and decoders
which may improve upon previously known codes in certain regimes. The encoders and …

The growing number of Internet of Thing (IoT) and Ultra-Reliable Low Latency
Communications (URLCC) use cases in next generation communication networks calls for …

Channel coding and modulation are two fundamental building blocks of physical layer
wireless communications. We propose a neural network based end-to-end communication …

Recently, deep learning based end-to-end communication systems have been developed,
where both the transmitter and the receiver are represented as deep neural networks (DNN) …