… , and game theory to optimize the performance of federated learning over wireless networks.
In the final part, we present several applications of federated learning in wireless networks. …

… wireless networks on the performance of FL, we illustrate that for maximum performance, in
terms of bandwidth efficiency and learning time, both FL and the underlying wireless network …

… introduction about federated learning and its fundamentals. We then highlighted many use
cases of federated learning in UAV-enabled networks ranging from 5G networks and beyond, …

… In this paper, we consider the deployment of federated learning in wireless networks, which
can be implemented via the interactions between a server and multiple clients. In particular, …

The conventional federated learning (FL) framework usually assumes synchronous reception
and fusion of all the local models at the central aggregator and synchronous updating and …

… —Federated learning (FL) has recently become one of the hottest focuses in wireless edge
networks … In FL, UEs train local machine learning models and transmit them to an aggregator, …

… of training federated learning (FL) algorithms over a realistic wireless network is studied. In
… over wireless networks by jointly considering FL and wireless metrics and factors. To our best …

… a wireless federated learning system, in which a server (eg, a base station) is connected to
𝐾 mobile devices (eg, mobile phones) via a wireless network. The primary learning task is to …

… learning (ML). However, the data originating from massive IoT devices are commonly generated
and stored in a distributed manner over wireless networks … learning, federated learning (…

Federated learning, as a promising machine learning … In federated learning, training data
is widely distributed and … to frauds in tasks of federated learning. The workers may perform …