[HTML][HTML] Federated learning for 6G: Applications, challenges, and opportunities
Standard machine-learning approaches involve the centralization of training data in a data
center, where centralized machine-learning algorithms can be applied for data analysis and …
center, where centralized machine-learning algorithms can be applied for data analysis and …
Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Gradient and channel aware dynamic scheduling for over-the-air computation in federated edge learning systems
To satisfy the expected plethora of computation-heavy applications, federated edge learning
(FEEL) is a new paradigm featuring distributed learning to carry the capacities of low-latency …
(FEEL) is a new paradigm featuring distributed learning to carry the capacities of low-latency …
A survey of beam management for mmWave and THz communications towards 6G
Communication in millimeter wave (mmWave) and even terahertz (THz) frequency bands is
ushering in a new era of wireless communications. Beam management, namely initial …
ushering in a new era of wireless communications. Beam management, namely initial …
Optimized power control design for over-the-air federated edge learning
Over-the-air federated edge learning (Air-FEEL) has emerged as a communication-efficient
solution to enable distributed machine learning over edge devices by using their data locally …
solution to enable distributed machine learning over edge devices by using their data locally …
Communication-efficient distributed learning: An overview
Distributed learning is envisioned as the bedrock of next-generation intelligent networks,
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
Federated learning in multi-RIS-aided systems
The fundamental communication paradigms in the next-generation mobile networks are
shifting from connected things to connected intelligence. The potential result is that current …
shifting from connected things to connected intelligence. The potential result is that current …
Integrated sensing, communication, and computation over-the-air: MIMO beamforming design
To support the unprecedented growth of the Internet of Things (IoT) applications,
tremendous data need to be collected by the IoT devices and delivered to the server for …
tremendous data need to be collected by the IoT devices and delivered to the server for …
Toward 6G Extreme Connectivity: Architecture, Key Technologies and Experiments
Sixth-generation (6G) networks are evolving toward new features and order-of-magnitude
enhancement of systematic performance metrics compared to the current 5G. In particular …
enhancement of systematic performance metrics compared to the current 5G. In particular …
Federated feature selection for horizontal federated learning in iot networks
Under horizontal federated learning (HFL) in the Internet of Things (IoT) scenarios, different
user data sets have significant similarities on the feature spaces, the final goal is to build a …
user data sets have significant similarities on the feature spaces, the final goal is to build a …