Artificial Intelligence in 6G Wireless Networks: Opportunities, Applications, and Challenges

A Alhammadi, I Shayea, AA El-Saleh… - … Journal of Intelligent …, 2024 - Wiley Online Library
Wireless technologies are growing unprecedentedly with the advent and increasing
popularity of wireless services worldwide. With the advancement in technology, profound …

Federated machine learning for intelligent IoT via reconfigurable intelligent surface

K Yang, Y Shi, Y Zhou, Z Yang, L Fu, W Chen - IEEE network, 2020 - ieeexplore.ieee.org
Intelligent Internet of Things (IoT) will be transformative with the advancement of artificial
intelligence and high-dimensional data analysis, shifting from" connected things" to" …

[HTML][HTML] Applicability of deep reinforcement learning for efficient federated learning in massive iot communications

P Tam, R Corrado, C Eang, S Kim - Applied Sciences, 2023 - mdpi.com
To build intelligent model learning in conventional architecture, the local data are required to
be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage …

Transfer learning for wireless networks: A comprehensive survey

CT Nguyen, N Van Huynh, NH Chu… - Proceedings of the …, 2022 - ieeexplore.ieee.org
With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

Federated learning with cooperating devices: A consensus approach for massive IoT networks

S Savazzi, M Nicoli, V Rampa - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Federated learning (FL) is emerging as a new paradigm to train machine learning (ML)
models in distributed systems. Rather than sharing and disclosing the training data set with …

Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions

Q Duan, J Huang, S Hu, R Deng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …

Transfer learning for future wireless networks: A comprehensive survey

CT Nguyen, N Van Huynh, NH Chu, YM Saputra… - arXiv preprint arXiv …, 2021 - arxiv.org
With outstanding features, Machine Learning (ML) has been the backbone of numerous
applications in wireless networks. However, the conventional ML approaches have been …

Federated learning for resource-constrained iot devices: Panoramas and state of the art

A Imteaj, K Mamun Ahmed, U Thakker, S Wang… - Federated and Transfer …, 2022 - Springer
Nowadays, devices are equipped with advanced sensors with higher processing and
computing capabilities. Besides, widespread Internet availability enables communication …

[图书][B] Recent trends and advances in wireless and IoT-enabled networks

MA Jan, F Khan, M Alam - 2019 - Springer
This book provides detailed information about the recent trends and advancements in
Information and Communications Technologies. The Information and Communications …

[HTML][HTML] A Comprehensive Overview of IoT-Based Federated Learning: Focusing on Client Selection Methods

N Khajehali, J Yan, YW Chow, M Fahmideh - Sensors, 2023 - mdpi.com
The integration of the Internet of Things (IoT) with machine learning (ML) is revolutionizing
how services and applications impact our daily lives. In traditional ML methods, data are …