… a new wireless communication … learning and provide potential federated learning applications
for 6G. We then describe key technical challenges, the corresponding federated learning …

… of wireless … learning model has emerged, namely federated learning (FL), that allows a
decoupling of data acquisition and computation at the central unit. Unlike centralized learning …

… network to construct a cooperative communication platform for supporting FL model
transmission. In [15], the authors developed a federated learning based spiking neural network. …

… 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 limited wireless resources (eg, bandwidth) and unreliable wireless channels. Thus,
this calls for a new design principle for FL from both learning and wireless communication …

… and security of federated learning in the field of wireless communication. Mohammad et al.
[… of federated learning in wireless network and edge computing, and established a federated …

… Federated learning (FL) is an emerging paradigm that enables multiple devices to collaborate
in training machine learning (ML) models without having to share their possibly private …

… is federated learning (FL), which enables the devices to train a common machine learning
… In particular, the essential requirements for applying FL to wireless communications are first …

… , a new machine learning framework called Federated Learning (FL) has … federated learning
over wireless communication networks,” IEEE Transactions on Wireless Communications…

This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO)
networks to support any federated learning (FL) framework. This scheme allows …