Machine learning in beyond 5G/6G networks—State-of-the-art and future trends

VP Rekkas, S Sotiroudis, P Sarigiannidis, S Wan… - Electronics, 2021 - mdpi.com
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …

Unveiling the Potential of Artificial Intelligence and Machine Learning in the 5G Network Landscape: A Comprehensive Review

S Rizvi - Asian Journal of Research in Computer …, 2023 - publications.article4sub.com
Exploring successful case studies, scholars and industry experts concur that artificial
intelligence (AI) and 5G technology, as holistic solutions, exhibit remarkable efficiency. The …

Thirty years of machine learning: The road to Pareto-optimal wireless networks

J Wang, C Jiang, H Zhang, Y Ren… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …

Network Selection over 5G-Advanced Heterogeneous Networks Based on Federated Learning and Cooperative Game Theory

CC González, EF Pupo, E Iradier… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
5G-Advanced and Beyond claims a 3D ecosystem with cooperation between terrestrial and
non-terrestrial networks to achieve seamless coverage, improve capacity, and enable …

A federated deep learning empowered resource management method to optimize 5G and 6G quality of services (QoS)

H Alsulami, SH Serbaya… - Wireless …, 2022 - Wiley Online Library
The quality of service (QoS) in 5G/6G communication enormously depends upon the
mobility and agility of the network architecture. An increase in the possible uses of 5G …

A survey of machine learning algorithms for 6G wireless networks

A Patil, S Iyer, RJ Pandya - arXiv preprint arXiv:2203.08429, 2022 - arxiv.org
The primary focus of Artificial Intelligence/Machine Learning (AI/ML) integration within the
wireless technology is to reduce capital expenditures, optimize network performance, and …

Intelligent user-centric network selection: A model-driven reinforcement learning framework

X Wang, J Li, L Wang, C Yang, Z Han - IEEE Access, 2019 - ieeexplore.ieee.org
Ultra-dense heterogeneous networks, as a novel network architecture in the fifth-generation
mobile communication system (5G), promise ubiquitous connectivity and smooth …

On softwarization of intelligence in 6G networks for ultra-fast optimal policy selection: Challenges and opportunities

S Hashima, ZM Fadlullah, MM Fouda… - IEEE …, 2022 - ieeexplore.ieee.org
The emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gb/s
rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial …

Applications of deep learning and deep reinforcement learning in 6G networks

TH Nguyen, H Park, K Seol, S So… - … on Ubiquitous and …, 2023 - ieeexplore.ieee.org
As the demand for data-driven applications and emerging technologies such as extended
reality, autonomous vehicles, and the Internet of Things (IoT) continues to grow, the …

[PDF][PDF] Special topic on computational radio intelligence: One key for 6G wireless

W JIANG, FL LUO - ZTE Communications, 2020 - zte.magtechjournal.com
The year of 2019 is the first deployment year of the fifth generation (5G) mobile
communications. As we are writing the editorial for this special issue, a list of coun⁃ tries …