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 …

Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial

A Feriani, E Hossain - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …

Distributed machine learning for wireless communication networks: Techniques, architectures, and applications

S Hu, X Chen, W Ni, E Hossain… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Distributed machine learning (DML) techniques, such as federated learning, partitioned
learning, and distributed reinforcement learning, have been increasingly applied to wireless …

A survey on resource management for 6G heterogeneous networks: current research, future trends, and challenges

HF Alhashimi, MHDN Hindia, K Dimyati, EB Hanafi… - Electronics, 2023 - mdpi.com
The sixth generation (6G) mobile communication system is expected to meet the different
service needs of modern communication scenarios. Heterogeneous networks (HetNets) …

Generative AI for the optimization of next-generation wireless networks: Basics, state-of-the-art, and open challenges

F Khoramnejad, E Hossain - IEEE Communications Surveys & …, 2025 - ieeexplore.ieee.org
Next-generation (xG) wireless networks, with their complex and dynamic nature, present
significant challenges to using traditional optimization techniques. Generative Artificial …

A survey of machine learning applications to handover management in 5G and beyond

MS Mollel, AI Abubakar, M Ozturk, SF Kaijage… - IEEE …, 2021 - ieeexplore.ieee.org
Handover (HO) is one of the key aspects of next-generation (NG) cellular communication
networks that need to be properly managed since it poses multiple threats to quality-of …

Empowering non-terrestrial networks with artificial intelligence: A survey

A Iqbal, ML Tham, YJ Wong, G Wainer, YX Zhu… - IEEE …, 2023 - ieeexplore.ieee.org
6G networks can support global, ubiquitous and seamless connectivity through the
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …

Joint sensing, communication, and AI: A trifecta for resilient THz user experiences

C Chaccour, W Saad, M Debbah… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this paper a novel joint sensing, communication, and artificial intelligence (AI) framework
is proposed so as to optimize extended reality (XR) experiences over terahertz (THz) …

Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends

HMF Noman, E Hanafi, KA Noordin, K Dimyati… - IEEE …, 2023 - ieeexplore.ieee.org
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …

Energy-efficient user association in mmWave/THz ultra-dense network via multi-agent deep reinforcement learning

J Moon, S Kim, H Ju, B Shim - IEEE Transactions on Green …, 2023 - ieeexplore.ieee.org
As a key enabler for 5G and 6G wireless communications, millimeter-wave (mmWave) and
terahertz (THz) ultra-dense network (UDN) has received a great deal of attention recently …