A learning approach for production-aware 5G slicing in private industrial networks
Industrial scenarios comprise multiple devices executing periodic, mutually-dependent tasks
with challenging communications requirements. 5G technology and RAN slicing make it …
with challenging communications requirements. 5G technology and RAN slicing make it …
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 …
On the specialization of fdrl agents for scalable and distributed 6g ran slicing orchestration
Network slicing enables multiple virtual networks to be instantiated and customized to meet
heterogeneous use case requirements over 5G and beyond network deployments …
heterogeneous use case requirements over 5G and beyond network deployments …
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 …
Reinforcement learning for dynamic resource optimization in 5G radio access network slicing
The paper presents a reinforcement learning solution to dynamic resource allocation for 5G
radio access network slicing. Available communication resources (frequency-time blocks …
radio access network slicing. Available communication resources (frequency-time blocks …
Real-time network slicing with uncertain demand: A deep learning approach
Practical and efficient network slicing often faces real-time dynamics of network resources
and uncertain customer demands. This work provides an optimal and fast resource slicing …
and uncertain customer demands. This work provides an optimal and fast resource slicing …
Multi-tenant cross-slice resource orchestration: A deep reinforcement learning approach
With the cellular networks becoming increasingly agile, a major challenge lies in how to
support diverse services for mobile users (MUs) over a common physical network …
support diverse services for mobile users (MUs) over a common physical network …
Uncertainty-aware RAN slicing via machine learning predictions in next-generation networks
R Abozariba, MK Naeem… - 2020 IEEE 92nd …, 2020 - ieeexplore.ieee.org
Network slicing enables 5G network operators to offer diverse services in the form of end-to-
end isolated slices, over shared physical infrastructure. Wireless service providers are facing …
end isolated slices, over shared physical infrastructure. Wireless service providers are facing …
Deep reinforcement learning for adaptive network slicing in 5G for intelligent vehicular systems and smart cities
Intelligent vehicular systems and smart city applications are the fastest growing Internet-of-
Things (IoT) implementations at a compound annual growth rate of 30%. In view of the …
Things (IoT) implementations at a compound annual growth rate of 30%. In view of the …
Multi-agent deep reinforcement learning for slicing and admission control in 5G C-RAN
M Sulaiman, A Moayyedi… - NOMS 2022-2022 …, 2022 - ieeexplore.ieee.org
5G Cloud Radio Access Networks (C-RANs) facilitate new forms of flexible resource
management as dynamic RAN function splitting and placement. Virtualized RAN functions …
management as dynamic RAN function splitting and placement. Virtualized RAN functions …