As an entirely-new paradigm to design the communication systems, deep learning (DL), an
approach that the machine learns the desired wireless function, has received much attention …

Deep learning (DL) has been gradually applied to wireless communication and has
achieved remarkable results. However, training a DL model requires numerous data, and an …

Generative adversarial network (GAN) has attracted wide attention because of its
remarkable ability to learn high-dimensional and complex data distributions based on game …

As a revolutionary generative paradigm of deep learning, generative adversarial networks
(GANs) have been widely applied in various fields to synthesize realistic data. However, it is …

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 …

As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …

Generally speaking, artificial intelligent (AI) models are trained under special learning
hypotheses, especially the one that statistics of the training data are static during the training …

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 …

Deep learning based on artificial neural networks (ANNs) is a powerful machine-learning
method that, in recent years, has been successfully used to realize tasks such as image …

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 …