[HTML][HTML] Deep reinforcement learning for resource management on network slicing: A survey
JA Hurtado Sánchez, K Casilimas… - Sensors, 2022 - mdpi.com
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
Federated learning-empowered mobile network management for 5G and beyond networks: From access to core
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …
integrated communication and computing platform that will enable multipurpose and …
Digital twin enhanced federated reinforcement learning with lightweight knowledge distillation in mobile networks
The high-speed mobile networks offer great potentials to many future intelligent applications,
such as autonomous vehicles in smart transportation systems. Such networks provide the …
such as autonomous vehicles in smart transportation systems. Such networks provide the …
DRL-based joint resource allocation and device orchestration for hierarchical federated learning in NOMA-enabled industrial IoT
Federated learning (FL) provides a new paradigm for protecting data privacy in Industrial
Internet of Things (IIoT). To reduce network burden and latency brought by FL with a …
Internet of Things (IIoT). To reduce network burden and latency brought by FL with a …
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 …
A survey on explainable ai for 6g o-ran: Architecture, use cases, challenges and research directions
The recent O-RAN specifications promote the evolution of RAN architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …
Federated deep reinforcement learning for task scheduling in heterogeneous autonomous robotic system
Autonomous robotics play a central role in smart logistics where robots can replace or aid
humans in all kinds of tasks, such as items picking, moving, and storing. In this paper, we …
humans in all kinds of tasks, such as items picking, moving, and storing. In this paper, we …
Network-aided intelligent traffic steering in 6g O-RAN: A multi-layer optimization framework
To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G
networks, considerable efforts have been made in standardization and development of open …
networks, considerable efforts have been made in standardization and development of open …
[HTML][HTML] Recent advances in machine learning for network automation in the o-ran
The evolution of network technologies has witnessed a paradigm shift toward open and
intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as …
intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as …