… algorithm in wireless Internet-of-Things (IoT) networks to mini… shift in bandwidth-constrained
learning wireless IoT networks. … We consider an FL-supported wireless IoT network consist…

… and the limited capabilities of mobile devices in a wireless communication system calls for
the appearance of federated learning (FL). As a distributed machine learning (ML) method, FL …

… This paper proposes a federated learning intrusion detection model called FedAGRU that
adopts to wireless edge networks. FedAGRU uses the computing resources of edge devices …

… is federated learning (FL), which enables the devices to train a common machine learning
model without … Wireless devices obtain their own private learning networks through RL in new …

… In this section, we will go through a brief overview of the theoretical aspects of both
centralized learning, distributed learning and federated learning. 4.1 Centralized learning …

… model training framework named federated learning (FL) [6], … However, when implementing
FL over wireless networks, … the learning performance, especially when the learning task is …

… federated learning (FL) in a classic wireless network, where learning clients share a common
wireless link to a coordinating server to perform federated model training using their local …

… resource-constrained nature of the wireless medium. In this paper, we propose a federated
learning algorithm that is suitable for cellular wireless networks. We prove its convergence, …

… on the distributed learning schemes. In [2], the authors proposed the federated learning (FL) …
, we will set up an integrated design principle for FL implementation over wireless networks. …

… communications, and intelligently manage wireless resource and devices [2], … wireless edge
users, the limited power and bandwidth available, and privacy concerns. Federated learning …