T Wang, CK Wen, H Wang, F Gao… - China …, 2017 - ieeexplore.ieee.org
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 …
C Mao, Z Mu, Q Liang, I Schizas, C Pan - IET Communications, 2023 - Wiley Online Library
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 …
Z Qin, H Ye, GY Li, BHF Juang - IEEE Wireless …, 2019 - ieeexplore.ieee.org
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 …
R Mitra, G Kaddoum - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
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 …