Machine learning techniques and a case study for intelligent wireless networks

H Yang, X Xie, M Kadoch - IEEE Network, 2020 - ieeexplore.ieee.org
With the widespread deployment of wireless technologies and IoT, 5G wireless networks will
support various communication connectivity and services for the huge number of wireless …

Machine learning paradigms for next-generation wireless networks

C Jiang, H Zhang, Y Ren, Z Han… - IEEE Wireless …, 2016 - ieeexplore.ieee.org
Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …

Artificial intelligence enabled Internet of Things: Network architecture and spectrum access

H Song, J Bai, Y Yi, J Wu, L Liu - IEEE Computational …, 2020 - ieeexplore.ieee.org
The explosive growth of wireless devices motivates the development of the internet-of-things
(IoT), which is capable of interconnecting massive and diverse" things" via wireless …

Artificial-intelligence-enabled intelligent 6G networks

H Yang, A Alphones, Z Xiong, D Niyato, J Zhao… - IEEE …, 2020 - ieeexplore.ieee.org
With the rapid development of smart terminals and infrastructures, as well as diversified
applications (eg, virtual and augmented reality, remote surgery and holographic projection) …

Reinforcement and deep reinforcement learning for wireless Internet of Things: A survey

MS Frikha, SM Gammar, A Lahmadi… - Computer Communications, 2021 - Elsevier
Nowadays, many research studies and industrial investigations have allowed the integration
of the Internet of Things (IoT) in current and future networking applications by deploying a …

Radio and energy resource management in renewable energy-powered wireless networks with deep reinforcement learning

HS Lee, DY Kim, JW Lee - IEEE Transactions on Wireless …, 2022 - ieeexplore.ieee.org
In this paper, we study radio and energy resource management in renewable energy-
powered wireless networks, where base stations (BSs) are powered by both on-grid and …

[PDF][PDF] Thirty years of machine learning: The road to pareto-optimal next-generation wireless networks

J Wang, C Jiang, H Zhang, Y Ren… - arXiv preprint arXiv …, 2019 - researchgate.net
Next-generation wireless networks (NGWN) have a substantial potential in terms of
supporting a broad range of complex compelling applications both in military and civilian …

Learning paradigms for communication and computing technologies in IoT systems

W Ejaz, M Basharat, S Saadat, AM Khattak… - Computer …, 2020 - Elsevier
Wireless communication and computation technologies are becoming increasingly complex
and dynamic due to the sophisticated and ubiquitous Internet of things (IoT) applications …

Deep learning for intelligent wireless networks: A comprehensive survey

Q Mao, F Hu, Q Hao - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
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 …

AIF: An artificial intelligence framework for smart wireless network management

G Cao, Z Lu, X Wen, T Lei, Z Hu - IEEE Communications …, 2017 - ieeexplore.ieee.org
To solve the policy optimizing problem in many scenarios of smart wireless network
management using a single universal algorithm, this letter proposes a universal learning …