Intelligible Protocol Learning for Resource Allocation in 6G O-RAN Slicing
F Rezazadeh, H Chergui, S Siddiqui… - IEEE Wireless …, 2024 - ieeexplore.ieee.org
An adaptive standardized protocol is essential for addressing inter-slice resource contention
and conflict in network slicing. Traditional protocol standardization is a cumbersome task …
and conflict in network slicing. Traditional protocol standardization is a cumbersome task …
Explanation-Guided Deep Reinforcement Learning for Trustworthy 6G RAN Slicing
F Rezazadeh, H Chergui… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The complexity of emerging sixth-generation (6G) wireless networks has sparked an
upsurge in adopting artificial intelligence (AI) to underpin the challenges in network …
upsurge in adopting artificial intelligence (AI) to underpin the challenges in network …
Communication and computation O-RAN resource slicing for URLLC services using deep reinforcement learning
A Filali, B Nour, S Cherkaoui… - IEEE Communications …, 2023 - ieeexplore.ieee.org
The evolution of the future beyond-5G/6G networks toward a service-aware network is
based on network slicing technology. With network slicing, communication service providers …
based on network slicing technology. With network slicing, communication service providers …
SliceOps: Explainable MLOps for Streamlined Automation-Native 6G Networks
Sixth-generation (6G) network slicing is the backbone of future communications systems. It
inaugurates the era of extreme ultra-reliable and low-latency communication (xURLLC), and …
inaugurates the era of extreme ultra-reliable and low-latency communication (xURLLC), and …
Edge-AI Empowered Dynamic VNF Splitting in O-RAN Slicing: A Federated DRL Approach
This letter highlights the combined advantages of Open Radio Access Network (O-RAN) and
distributed Artificial Intelligence (AI) in network slicing. O-RAN's virtualization and …
distributed Artificial Intelligence (AI) in network slicing. O-RAN's virtualization and …
Towards Scalable and Efficient Hierarchical Deep Reinforcement Learning for 5G RAN Slicing
As an emerging and promising network paradigm, network slicing creates multiple logical
networks on shared infrastructure to provide services with customized Quality-of-Service …
networks on shared infrastructure to provide services with customized Quality-of-Service …
Flexible RAN Slicing in Open RAN With Constrained Multi-Agent Reinforcement Learning
M Zangooei, M Golkarifard, M Rouili… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Network slicing enables the provision of customized services in next-generation mobile
networks. Accordingly, the network is divided into logically isolated networks that share …
networks. Accordingly, the network is divided into logically isolated networks that share …
Knowledge transfer based radio and computation resource allocation for 5G RAN slicing
H Zhou, M Erol-Kantarci - 2022 IEEE 19th Annual Consumer …, 2022 - ieeexplore.ieee.org
To implement network slicing in 5G, resource allocation is a key function to allocate limited
network resources such as radio and computation resources to multiple slices. However, the …
network resources such as radio and computation resources to multiple slices. However, the …
GAN-powered deep distributional reinforcement learning for resource management in network slicing
Network slicing is a key technology in 5G communications system. Its purpose is to
dynamically and efficiently allocate resources for diversified services with distinct …
dynamically and efficiently allocate resources for diversified services with distinct …
HexRAN: A programmable multi-RAT platform for network slicing in the open RAN ecosystem
In recent years, the Open Radio Access Network (O-RAN) architecture has emerged as a
major driving force for programmability in cellular networks and is recognized as a key …
major driving force for programmability in cellular networks and is recognized as a key …