A Collaborative Data-Driven Intelligence for Future Wireless Networks

R Ali, HS Kim - Data-Driven Intelligence in Wireless Networks, 2023 - taylorfrancis.com
Future wireless networks, such as IEEE 802.11 be (Wi-Fi 7), are vital to provide ubiquitous
ultra-reliable and low latency communication services with massively connected devices to …

A federated reinforcement learning framework for incumbent technologies in beyond 5G networks

R Ali, YB Zikria, S Garg, AK Bashir, MS Obaidat… - IEEE …, 2021 - ieeexplore.ieee.org
Incumbent wireless technologies for futuristic fifth generation (5G) and beyond 5G (B5G)
networks, such as IEEE 802.11 ax (WiFi), are vital to provide ubiquitous ultra-reliable and …

A federated reinforcement learning framework for link activation in multi-link Wi-Fi networks

R Ali, B Bellalta - … IEEE International Black Sea Conference on …, 2023 - ieeexplore.ieee.org
Next-generation Wi-Fi networks are looking forward to introducing new features like multi-
link operation (MLO) to both achieve higher throughput and lower latency. However, given …

Advanced Reinforcement Learning-Based Optimization Techniques for Wireless Access Networks

P Iturria Rivera - 2024 - ruor.uottawa.ca
Next-generation wireless networks have grown increasingly complex over the years due to
the continuous demand generated by newer services like Extended Reality (XR) …

Reinforcement Learning for Optimizing Wi-Fi Access Channel Selection

H Nguyen, DL Pham, MH Doan, TTS Nguyen… - … Conference, ICCCI 2021 …, 2021 - Springer
Wi-Fi's success is largely a testament to its cost-effectiveness, convenience, and ease of
integration with other networks. Wi-Fi allows a suddenly increased number of users to …

Deep reinforcement learning paradigm for dense wireless networks in smart cities

R Ali, YB Zikria, BS Kim, SW Kim - Smart cities performability, cognition, & …, 2020 - Springer
Wireless local area networks (WLANs) are widely deployed for Internet-centric data
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …

Channel Selection for Wi-Fi 7 Multi-Link Operation via Optimistic-Weighted VDN and Parallel Transfer Reinforcement Learning

PE Iturria-Rivera, M Chenier… - 2023 IEEE 34th …, 2023 - ieeexplore.ieee.org
Dense and unplanned IEEE 802.11 Wireless Fidelity (Wi-Fi) deployments and the
continuous increase of throughput and latency stringent services for users have led to …

6 Applications of Reinforcement Learning

D Shrivastava, A Gupta, B Verma - Applications of Computational …, 2023 - books.google.com
A new wireless communication paradigm, the sixth generation (6G) framework, with full
Artificial Intelligence (AI) support, is planned for deployment by the end of this decade (1) …

Reinforcement learning meets wireless networks: A layering perspective

Y Chen, Y Liu, M Zeng, U Saleem, Z Lu… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Driven by the soaring traffic demand and the growing diversity of mobile services, wireless
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …

Federated Reinforcement Learning with Knowledge Transfer for Network Selection in Hybrid WiFi-VLC Networks

AM Alenezi, KA Hamdi - IEEE Transactions on Artificial …, 2023 - ieeexplore.ieee.org
The dramatic growth of mobile data demand may impose a heavy traffic burden in indoor
environments such that conventional radio frequency wireless networks might not be …