Security and privacy for 6G: A survey on prospective technologies and challenges
Sixth-generation (6G) mobile networks will have to cope with diverse threats on a space-air-
ground integrated network environment, novel technologies, and an accessible user …
ground integrated network environment, novel technologies, and an accessible user …
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 …
Federated reinforcement learning: Techniques, applications, and open challenges
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL),
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …
Deep reinforcement learning assisted federated learning algorithm for data management of IIoT
The continuous expanded scale of the industrial Internet of Things (IIoT) leads to IIoT
equipments generating massive amounts of user data every moment. According to the …
equipments generating massive amounts of user data every moment. According to the …
Dynamic pricing and energy management for profit maximization in multiple smart electric vehicle charging stations: A privacy-preserving deep reinforcement learning …
S Lee, DH Choi - Applied Energy, 2021 - Elsevier
Profit maximization of electric vehicle charging station (EVCS) operation yields an
increasing investment for the deployment of EVCSs, thereby increasing the penetration of …
increasing investment for the deployment of EVCSs, thereby increasing the penetration of …
Edge-native intelligence for 6G communications driven by federated learning: A survey of trends and challenges
New technological advancements in wireless networks have enlarged the number of
connected devices. The unprecedented surge of data volume in wireless systems …
connected devices. The unprecedented surge of data volume in wireless systems …
Artificial intelligence-assisted network slicing: Network assurance and service provisioning in 6G
6G networks are expected to provide instant global connectivity and enable the transition
from “connected things” to “connected intelligence,” where promising network slicing can …
from “connected things” to “connected intelligence,” where promising network slicing can …
Beam management in ultra-dense mmWave network via federated reinforcement learning: An intelligent and secure approach
Deploying ultra-dense networks that operate on millimeter wave (mmWave) band is a
promising way to address the tremendous growth on mobile data traffic. However, one key …
promising way to address the tremendous growth on mobile data traffic. However, one key …
Federated deep reinforcement learning for resource allocation in O-RAN slicing
Recently, open radio access network (O-RAN) has become a promising technology to
provide an open environment for network vendors and operators. Coordinating the x …
provide an open environment for network vendors and operators. Coordinating the x …
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 …