Dynamic SDN-based radio access network slicing with deep reinforcement learning for URLLC and eMBB services
A Filali, Z Mlika, S Cherkaoui… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Radio access network (RAN) slicing is a key technology that enables 5G network to support
heterogeneous requirements of generic services, namely ultra-reliable low-latency …
heterogeneous requirements of generic services, namely ultra-reliable low-latency …
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 …
Intelligent radio access network slicing for service provisioning in 6G: A hierarchical deep reinforcement learning approach
Network slicing is a key paradigm in 5G and is expected to be inherited in future 6G
networks for the concurrent provisioning of diverse quality of service (QoS). Unfortunately …
networks for the concurrent provisioning of diverse quality of service (QoS). Unfortunately …
Resource slicing for eMBB and URLLC services in radio access network using hierarchical deep learning
M Setayesh, S Bahrami… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network slicing is a promising technique for wireless service providers to support enhanced
mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services …
mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services …
Low-complexity distributed radio access network slicing: Algorithms and experimental results
Radio access network (RAN) slicing is an effective methodology to dynamically allocate
networking resources in 5G networks. One of the main challenges of RAN slicing is that it is …
networking resources in 5G networks. One of the main challenges of RAN slicing is that it is …
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 …
Joint multi-objective optimization for radio access network slicing using multi-agent deep reinforcement learning
Radio access network (RAN) slices can provide various customized services for next-
generation wireless networks. Thus, multiple performance metrics of different types of RAN …
generation wireless networks. Thus, multiple performance metrics of different types of RAN …
Intelligent resource scheduling for 5G radio access network slicing
It is widely acknowledged that network slicing can tackle the diverse use cases and
connectivity services of the forthcoming next-generation mobile networks (5G). Resource …
connectivity services of the forthcoming next-generation mobile networks (5G). Resource …
An intelligent self-sustained RAN slicing framework for diverse service provisioning in 5G-beyond and 6G networks
Network slicing is a key technology to support the concurrent provisioning of heterogeneous
Quality of Service (QoS) in the 5th Generation (5G)-beyond and the 6th Generation (6G) …
Quality of Service (QoS) in the 5th Generation (5G)-beyond and the 6th Generation (6G) …
Flexible resource block allocation to multiple slices for radio access network slicing using deep reinforcement learning
Y Abiko, T Saito, D Ikeda, K Ohta, T Mizuno… - IEEE …, 2020 - ieeexplore.ieee.org
In the fifth-generation of mobile communications, network slicing is used to provide an
optimal network for various services as a slice. In this paper, we propose a radio access …
optimal network for various services as a slice. In this paper, we propose a radio access …