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 …
Reinforcement learning for intelligent healthcare systems: A review of challenges, applications, and open research issues
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare
expenditure and mortality rates. This calls for transforming healthcare systems away from …
expenditure and mortality rates. This calls for transforming healthcare systems away from …
Deep learning at the mobile edge: Opportunities for 5G networks
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …
storage, and analysis closer to the end user. The increased speeds and reduced delay …
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 …
Machine learning in network slicing—a survey
5G and beyond networks are expected to support a wide range of services, with highly
diverse requirements. Yet, the traditional “one-size-fits-all” network architecture lacks the …
diverse requirements. Yet, the traditional “one-size-fits-all” network architecture lacks the …
Federated learning and next generation wireless communications: A survey on bidirectional relationship
In order to meet the extremely heterogeneous requirements of the next generation wireless
communication networks, research community is increasingly dependent on using machine …
communication networks, research community is increasingly dependent on using machine …
Coordinated slicing and admission control using multi-agent deep reinforcement learning
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 …
Intelligent network slicing in V2X networks–A comprehensive review
The rise of the Internet of Things and autonomous systems has made connecting vehicles
more critical. Connected autonomous vehicles can create diverse communication networks …
more critical. Connected autonomous vehicles can create diverse communication networks …
Reinforcement learning for intelligent healthcare systems: A comprehensive survey
The rapid increase in the percentage of chronic disease patients along with the recent
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
Adversarial machine learning for flooding attacks on 5G radio access network slicing
Network slicing manages network resources as virtual resource blocks (RBs) for the 5G
Radio Access Network (RAN). Each communication request comes with quality of …
Radio Access Network (RAN). Each communication request comes with quality of …