Algorithmics and modeling aspects of network slicing in 5G and beyonds network: Survey

F Debbabi, R Jmal, LC Fourati, A Ksentini - IEEE Access, 2020 - ieeexplore.ieee.org
One of the key goals of future 5G networks is to incorporate many different services into a
single physical network, where each service has its logical network isolated from other …

Federated learning for 6g: Paradigms, taxonomy, recent advances and insights

MB Driss, E Sabir, H Elbiaze, W Saad - arxiv preprint arxiv:2312.04688, 2023 - arxiv.org
Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …

Towards secure and intelligent network slicing for 5g networks

F Salahdine, Q Liu, T Han - IEEE Open Journal of the Computer …, 2022 - ieeexplore.ieee.org
Network slicing is one of the emerging technologies allowing resource sharing among
different network entities in 5G networks. It enables delivering smart, critical, and multi …

Elastic O-RAN slicing for industrial monitoring and control: A distributed matching game and deep reinforcement learning approach

SF Abedin, A Mahmood, NH Tran… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this work, we design an elastic open radio access network (O-RAN) slicing for the
Industrial Internet of things (IIoT). Due to the rapid spread of IoT in the industrial use-cases …

Statistical federated learning for beyond 5G SLA-constrained RAN slicing

H Chergui, L Blanco… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A key enabler for both scalability and sustainability in beyond 5G (B5G) network slicing
consists on minimizing the exchange of raw monitoring data across different domains. This …

Decentralized federated reinforcement learning for user-centric dynamic TFDD control

Z Yin, Z Wang, J Li, M Ding, W Chen… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
The explosive growth of dynamic and heterogeneous data traffic brings great challenges for
5G and beyond mobile networks. To enhance the network capacity and reliability, we …

Towards Bridging the FL Performance-Explainability Trade-Off: A Trustworthy 6G RAN Slicing Use-Case

S Roy, H Chergui, C Verikoukis - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the context of sixth-generation (6G) networks, where diverse network slices coexist, the
adoption of AI-driven zero-touch management and orchestration (MANO) becomes crucial …

Joint Explainability and Sensitivity-Aware Federated Deep Learning for Transparent 6G RAN Slicing

S Roy, F Rezazadeh, H Chergui… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
In recent years, wireless networks are evolving complex, which upsurges the use of zero-
touch artificial intelligence (AI)-driven network automation within the telecommunication …

Overview of AI-based Algorithms for Network Slicing Resource Management in B5G and 6G

F Debbabi, J Rihab, L Chaari… - 2022 International …, 2022 - ieeexplore.ieee.org
We are now in the early stage of the Fifth Generation (5G) commercialization, and its
improved capabilities and unique features will revolutionize the present wireless network …

TEFL: Turbo Explainable Federated Learning for 6G Trustworthy Zero-Touch Network Slicing

S Roy, H Chergui, C Verikoukis - arxiv preprint arxiv:2210.10147, 2022 - arxiv.org
Sixth-generation (6G) networks anticipate intelligently supporting a massive number of
coexisting and heterogeneous slices associated with various vertical use cases. Such a …