Holistic network virtualization and pervasive network intelligence for 6G

X Shen, J Gao, W Wu, M Li, C Zhou… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

Ten challenges in advancing machine learning technologies toward 6G

N Kato, B Mao, F Tang, Y Kawamoto… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
As the 5G standard is being completed, academia and industry have begun to consider a
more developed cellular communication technique, 6G, which is expected to achieve high …

Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions

ME Morocho-Cayamcela, H Lee, W Lim - IEEE access, 2019 - ieeexplore.ieee.org
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …

Applications of deep reinforcement learning in communications and networking: A survey

NC Luong, DT Hoang, S Gong, D Niyato… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

Network intrusion detection for IoT security based on learning techniques

N Chaabouni, M Mosbah, A Zemmari… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …

Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges

F Tang, B Mao, N Kato, G Gui - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Data-driven deep learning for automatic modulation recognition in cognitive radios

Y Wang, M Liu, J Yang, G Gui - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) is an essential and challenging topic in the
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …

IoT connectivity technologies and applications: A survey

J Ding, M Nemati, C Ranaweera, J Choi - IEEE Access, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) is rapidly becoming an integral part of our life and also multiple
industries. We expect to see the number of IoT connected devices explosively grows and will …