With the ever improving computing capabilities and storage capacities of mobile devices in
line with evolving telecommunication network paradigms, there has been an explosion of …

Smart services based on the Internet of Things (IoT) are likely to grow in popularity in the
forthcoming years, necessitating the improvement of fifth-generation (5G) cellular networks …

The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …

Distributed machine learning (DML) techniques, such as federated learning, partitioned
learning, and distributed reinforcement learning, have been increasingly applied to wireless …

With the rapid advancements in edge computing and artificial intelligence, federated
learning (FL) has gained momentum as a promis⁃ ing approach to collaborative data …

With 5G cellular systems being actively deployed worldwide, the research community has
started to explore novel technological advances for the subsequent generation, ie, 6G. It is …

Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …

The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …

Federated learning (FL) is a swiftly evolving field within machine learning for collaboratively
training models at the network edge in a privacy-preserving fashion, without training data …

There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …