Multiple access techniques for intelligent and multifunctional 6G: Tutorial, survey, and outlook

B Clerckx, Y Mao, Z Yang, M Chen… - Proceedings of the …, 2024‏ - ieeexplore.ieee.org
Multiple access (MA) is a crucial part of any wireless system and refers to techniques that
make use of the resource dimensions (eg, time, frequency, power, antenna, code, and …

A survey on over-the-air computation

A Şahin, R Yang - IEEE Communications Surveys & Tutorials, 2023‏ - ieeexplore.ieee.org
Communication and computation are often viewed as separate tasks. This approach is very
effective from the perspective of engineering as isolated optimizations can be performed …

Survey: federated learning data security and privacy-preserving in edge-Internet of Things

H Li, L Ge, L Tian - Artificial Intelligence Review, 2024‏ - Springer
The amount of data generated owing to the rapid development of the Smart Internet of
Things is increasing exponentially. Traditional machine learning can no longer meet the …

Joint spectrum, precoding, and phase shifts design for RIS-aided multiuser MIMO THz systems

A Mehrabian, VWS Wong - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Terahertz (THz) wireless systems aim to support content-rich applications with ultra-high
data rate. Due to high molecular absorption, THz signals experience severe path loss over …

Federated learning via unmanned aerial vehicle

M Fu, Y Shi, Y Zhou - IEEE Transactions on Wireless …, 2023‏ - ieeexplore.ieee.org
Federated learning (FL) has emerged as a promising alternative to centralized machine
learning for exploiting large amounts of data generated by networks while ensuring data …

Online optimization for over-the-air federated learning with energy harvesting

Q An, Y Zhou, Z Wang, H Shan, Y Shi… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Federated learning (FL) is recognized as a promising privacy-preserving distributed
machine learning paradigm, given its potential to enable collaborative model training among …

Federated Edge Learning for 6G: Foundations, Methodologies, and Applications

M Tao, Y Zhou, Y Shi, J Lu, S Cui, J Lu… - Proceedings of the …, 2024‏ - ieeexplore.ieee.org
Artificial intelligence (AI) is envisioned to be natively integrated into the sixth-generation (6G)
mobile networks to support a diverse range of intelligent applications. Federated edge …

Federated fine-tuning for pre-trained foundation models over wireless networks

Z Wang, Y Zhou, Y Shi… - IEEE Transactions on …, 2025‏ - ieeexplore.ieee.org
Pre-trained foundation models (FMs), with extensive number of neurons, are key to
advancing next-generation intelligence services, where personalizing these models …

Graph attention-based MADRL for access control and resource allocation in wireless networked control systems

Z Wang, M Bennis, Y Zhou - IEEE Transactions on Wireless …, 2024‏ - ieeexplore.ieee.org
Wireless networked control systems (WNCS) offer great potential for revolutionizing the
industrial automation by enabling wireless coordination between sensors, decision centers …

A survey of graph-based resource management in wireless networks-part ii: Learning approaches

Y Dai, L Lyu, N Cheng, M Sheng, J Liu… - IEEE Transactions …, 2024‏ - ieeexplore.ieee.org
This two-part survey provides a comprehensive review of graph optimization and learning
for resource management in wireless networks. In Part I, we introduced the fundamentals of …