Advanced technologies are required in future mobile wireless networks to support services
with highly diverse requirements in terms of high data rate and reliability, low latency, and …

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 …

Intelligent communication is gradually becoming a mainstream direction. As a major branch
of machine learning, deep learning (DL) has been applied in physical layer communications …

With the rapid development of the communication industry in the fifth generation and the
advance towards the intelligent society of the sixth generation wireless networks, traditional …

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 …

DL has shown great potential to revolutionize communication systems. This article provides
an overview of the recent advancements in DL-based physical layer communications. DL …

Deep learning has proved itself to be a powerful tool to develop data-driven signal
processing algorithms for challenging engineering problems. By learning the key features …

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-learning (DL) has emerged as a powerful machine-learning technique for several
problems encountered in generic wireless communications. Also, random Fourier Features …

Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …