… devices with intelligent adaptive learning and reduce expensive traffic in SatCom, we
propose federated learning (FL) in LEO-based satellite communication networks. We first review …

… Abstract—We study federated learning (FL) at the wireless edge, where power-limited
devices with local datasets collaboratively train a joint model with the help of a remote parameter …

… —Implementing federated learning (FL) algorithms in wireless … of user mobility on the
learning performance. To fill this … the hierarchical federated learning (HFL) algorithm in wireless …

… To address the aforementioned issues, researchers have proposed a new distributed
model training framework called Federated Learning (FL) [6], [7]. A typical wireless FL system …

… edge networks, federated learning (FL) has been proposed as an attractive substitute for
centralized machine learning (ML). By collaboratively training a shared learning model at edge …

… The wireless federated learning system is illustrated in Fig. 1. We assume a federated learning
task of collaboratively training a ML model (eg, logistic regression or deep neural network …

… of wireless communication resources, in this letter, we propose a client scheduling strategy
for a wireless … In this section, we introduce the wireless channel and learning models used in …

… distributed learning architecture, a hybrid split and federated learning … , Net and AlexNet, in
wireless UAV networks, our results … higher learning accuracy than FL and less communication …

… WIRELESS FEDERATED LEARNING We consider a wireless federated learning system, in
… ) is connected to 𝐾 mobile devices (eg, mobile phones) via a wireless network. The primary …

… federated learning and its fundamentals. We then highlighted many use cases of federated
learning … Lim, ‘‘Machine learning for 5G/B5G mobile and wireless communications: Potential, …