The next generation of telecommunication networks will integrate the latest developments
and emerging advancements in telecommunications connectivity infrastructures. In this …

Federated learning (FL) as a promising edge-learning framework can effectively address the
latency and privacy issues by featuring distributed learning at the devices and model …

Today, patients are demanding a newer and more sophisticated health care system, one
that is more personalized and matches the speed of modern life. For the latency and energy …

In cellular federated edge learning (FEEL), multiple edge devices holding local data jointly
train a neural network by communicating learning updates with an access point without …

Emerging 5G cellular networks are expected to face a dramatic increase in the volume of
mobile traffic and IoT user requests due to the massive growth in mobile devices and the …

Federated Learning (FL) refers to distributed protocols that avoid direct raw data exchange
among the participating devices while training for a common learning task. This way, FL can …

With the deployment of 5G, researchers and experts begin to look forward to 6G. They
predict that 6G will be the key driving force for information interaction and social life after …

Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …

In this white paper we provide a vision for 6G Edge Intelligence. Moving towards 5G and
beyond the future 6G networks, intelligent solutions utilizing data-driven machine learning …

Edge intelligence, also called edge-native artificial intelligence (AI), is an emerging
technological framework focusing on seamless integration of AI, communication networks …