Deep learning for wireless physical layer: Opportunities and challenges

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 …

Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology

M Abd Elaziz, MAA Al‐qaness, A Dahou… - … : Data Mining and …, 2024 - Wiley Online Library
The sixth generation (6G) represents the next evolution in wireless communication
technology and is currently under research and development. It is expected to deliver faster …

Machine learning in 6G wireless communications

T Ohtsuki - IEICE Transactions on Communications, 2023 - search.ieice.org
Mobile communication systems are not only the core of the Information and Communication
Technology (ICT) infrastructure but also that of our social infrastructure. The 5th generation …

Applications of machine learning to cognitive radio networks

C Clancy, J Hecker, E Stuntebeck… - IEEE Wireless …, 2007 - ieeexplore.ieee.org
Cognitive radio offers the promise of intelligent radios that can learn from and adapt to their
environment. To date, most cognitive radio research has focused on policy-based radios that …

Wireless networks design in the era of deep learning: Model-based, AI-based, or both?

A Zappone, M Di Renzo… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper deals with the use of emerging deep learning techniques in future wireless
communication networks. It will be shown that the data-driven approaches should not …

Learning radio resource management in RANs: Framework, opportunities, and challenges

FD Calabrese, L Wang, E Ghadimi… - IEEE …, 2018 - ieeexplore.ieee.org
In the fifth generation (5G) of mobile broadband systems, radio resource management
(RRM) will reach unprecedented levels of complexity. To cope with the ever more …

Scalable learning paradigms for data-driven wireless communication

Y Xu, F Yin, W Xu, CH Lee, J Lin… - IEEE Communications …, 2020 - ieeexplore.ieee.org
The marriage of wireless big data and machine learning techniques revolutionizes wireless
systems by introducing data-driven philosophy. However, the ever exploding data volume …

Q-learning-enabled channel access in next-generation dense wireless networks for IoT-based eHealth systems

R Ali, YA Qadri, Y Bin Zikria, T Umer, BS Kim… - EURASIP Journal on …, 2019 - Springer
One of the key applications for the Internet of Things (IoT) is the eHealth service that targets
sustaining patient health information in digital environments, such as the Internet cloud with …

Machine learning for physical layer in 5G and beyond wireless networks: A survey

J Tanveer, A Haider, R Ali, A Kim - Electronics, 2021 - mdpi.com
Fifth-generation (5G) technology will play a vital role in future wireless networks. The
breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where …

Distributed intelligence in wireless networks

X Liu, J Yu, Y Liu, Y Gao, T Mahmoodi… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
The cloud-based solutions are becoming inefficient due to considerably large time delays,
high power consumption, and security and privacy concerns caused by billions of connected …