Intent-aware radio resource scheduling in a ran slicing scenario using reinforcement learning
Network slicing at the radio access network (RAN) domain, called RAN slicing, requires
elasticity, efficient resource sharing, and customization. In this scenario, radio resource …
elasticity, efficient resource sharing, and customization. In this scenario, radio resource …
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 …
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 …
Framework for slice-aware radio resource management utilizing artificial neural networks
For accommodating the heterogeneous services that are anticipated for the fifth-generation
(5G) mobile networks, the concept of network slicing serves as a key technology. Spanning …
(5G) mobile networks, the concept of network slicing serves as a key technology. Spanning …
Reinforcement learning for radio resource management in ran slicing: A survey
M Zangooei, N Saha, M Golkarifard… - IEEE Communications …, 2023 - ieeexplore.ieee.org
Dynamic radio resource allocation to network slices in mobile networks is challenging due to
the diverse requirements of RAN slices and the dynamic environment of wireless networks …
the diverse requirements of RAN slices and the dynamic environment of wireless networks …
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 …
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 …
Online convex optimization for efficient and robust inter-slice radio resource management
T Wang, S Wang - IEEE Transactions on Communications, 2021 - ieeexplore.ieee.org
Radio access network (RAN) slicing is one of the key technologies in 5G and beyond mobile
networks, where multiple logical subnets, ie, RAN slices, are allowed to run on top of the …
networks, where multiple logical subnets, ie, RAN slices, are allowed to run on top of the …
Energy-efficient deep reinforcement learning assisted resource allocation for 5G-RAN slicing
One of the pillars of the 5G architecture is network slicing, in which hardware, radio, and
power resources are virtualized as a logical network taking into account the requirements of …
power resources are virtualized as a logical network taking into account the requirements of …
Deep Reinforcement Learning for Optimization of RAN Slicing Relying on Control-and User-Plane Separation
The rapid development of radio access network (RAN) slicing and control-and user-plane
separation (CUPS) has created a new paradigm for future networks, namely CUPS-based …
separation (CUPS) has created a new paradigm for future networks, namely CUPS-based …