Accelerating reinforcement learning via predictive policy transfer in 6G RAN slicing
AM Nagib, H Abou-Zeid… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reinforcement Learning (RL) algorithms have recently been proposed to solve dynamic
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
Transfer learning-based accelerated deep reinforcement learning for 5G RAN slicing
AM Nagib, H Abou-Zeid… - 2021 IEEE 46th …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) algorithms have been recently proposed to solve
dynamic Radio Resource Management (RRM) problems in 5G networks. However, the slow …
dynamic Radio Resource Management (RRM) problems in 5G networks. However, the slow …
Advancing RAN slicing with offline reinforcement learning
Dynamic radio resource management (RRM) in wireless networks presents significant
challenges, particularly in the context of Radio Access Network (RAN) slicing. This …
challenges, particularly in the context of Radio Access Network (RAN) slicing. This …
Safe and accelerated deep reinforcement learning-based O-RAN slicing: A hybrid transfer learning approach
AM Nagib, H Abou-Zeid… - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
The open radio access network (O-RAN) architecture supports intelligent network control
algorithms as one of its core capabilities. Data-driven applications incorporate such …
algorithms as one of its core capabilities. Data-driven applications incorporate such …
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 …
Federated deep reinforcement learning for open ran slicing in 6g networks
A Abouaomar, A Taik, A Filali… - IEEE Communications …, 2022 - ieeexplore.ieee.org
Radio access network (RAN) slicing is a key element in enabling current 5G networks and
next-generation networks to meet the requirements of different services in various verticals …
next-generation networks to meet the requirements of different services in various verticals …
Learning radio resource management in RANs: Framework, opportunities, and challenges
In the fifth generation (5G) of mobile broadband systems, radio resource management
(RRM) will reach unprecedented levels of complexity. To cope with the ever more …
(RRM) will reach unprecedented levels of complexity. To cope with the ever more …
Reinforcement learning-based radio access network slicing for a 5G system with support for cellular V2X
HDR Albonda, J Pérez-Romero - … 2019, Poznan, Poland, June 11–12 …, 2019 - Springer
Abstract 5G mobile systems are expected to host a variety of services and applications such
as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) …
as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) …
Model-based reinforcement learning with kernels for resource allocation in RAN slices
Network slicing is a key feature of 5G and beyond networks, allowing the deployment of
separate logical networks (network slices), sharing a common underlying physical …
separate logical networks (network slices), sharing a common underlying physical …
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 …