A canonical wireless communication system consists of a transmitter and a receiver. The
information bit stream is transmitted after coding, modulation, and pulse shaping. Due to the …

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 …

Deep neural networks (DNNs) are state-of-the-art solutions for many machine learning
applications, and have been widely used on mobile devices. Running DNNs on …

The unprecedented requirements of IoT have made fine-grained optimization of spectrum
resources an urgent necessity. Thus, designing techniques able to extract knowledge from …

Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …

The recent revival of AI is revolutionizing almost every branch of science and technology.
Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of …

Future wireless communications are becoming increasingly complex with different radio
access technologies, transmission backhauls, and network slices, and they play an …

The research about deep learning application for physical layer has been received much
attention in recent years. In this paper, we propose a Deep Learning (DL) based channel …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Deep learning (DL) based autoencoder (AE) has been proposed recently as a promising,
and potentially disruptive approach to design the physical layer of beyond-5G …