On softwarization of intelligence in 6G networks for ultra-fast optimal policy selection: Challenges and opportunities
The emerging Sixth Generation (6G) communication networks promising 100 to 1000 Gb/s
rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial …
rates and ultra-low latency (1 millisecond) are anticipated to have native, embedded Artificial …
Green concerns in federated learning over 6G
As Information, Communications, and Data Technology (ICDT) are deeply integrated, the
research of 6G gradually rises. Meanwhile, federated learning (FL) as a distributed artificial …
research of 6G gradually rises. Meanwhile, federated learning (FL) as a distributed artificial …
Deep reinforcement learning for user association and resource allocation in heterogeneous cellular networks
Heterogeneous cellular networks can offload the mobile traffic and reduce the deployment
costs, which have been considered to be a promising technique in the next-generation …
costs, which have been considered to be a promising technique in the next-generation …
Resource allocation in mobility-aware federated learning networks: A deep reinforcement learning approach
Federated learning allows mobile devices, ie, workers, to use their local data to
collaboratively train a global model required by the model owner. Federated learning thus …
collaboratively train a global model required by the model owner. Federated learning thus …
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 …
Coordinated reinforcement learning for optimizing mobile networks
Mobile networks are composed of many base stations and for each of them many
parameters must be optimized to provide good services. Automatically and dynamically …
parameters must be optimized to provide good services. Automatically and dynamically …
Client selection and bandwidth allocation in wireless federated learning networks: A long-term perspective
This paper studies federated learning (FL) in a classic wireless network, where learning
clients share a common wireless link to a coordinating server to perform federated model …
clients share a common wireless link to a coordinating server to perform federated model …
Q-learning-enabled channel access in next-generation dense wireless networks for IoT-based eHealth systems
One of the key applications for the Internet of Things (IoT) is the eHealth service that targets
sustaining patient health information in digital environments, such as the Internet cloud with …
sustaining patient health information in digital environments, such as the Internet cloud with …
Smart multi-RAT access based on multiagent reinforcement learning
The ongoing increasing traffic in the era of big data yields unprecedented demands in user
experience and network capacity expansion. The users of next generation mobile networks …
experience and network capacity expansion. The users of next generation mobile networks …
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 …