… study federated machine learning at the wireless network edge, where limited power wireless
… We consider a bandwidth-limited fading multiple access channel (MAC) from the wireless …

… To enable training on a diverse ensemble of fading realizations, we propose a federated
training scheme, in which multiple users collaborate to jointly learn a universal datadriven …

… In Section III, we detail the local computing and parameter update process to run FL in
wireless networks. In Section IV, we analyze the convergence rate of federated learning under …

… to train a learning model locally. … learning frameworks is federated learning (FL) developed
in [5]. FL is a distributed machine learning method that enables users to collaboratively learn …

… learning in resource and privacy-constrained systems such as the Internet of Things, federated
learning … enabling edge devices to train a shared learning model while promoting privacy. …

… by complex fading channel hn,i. Due … federated learning framework rooted in the alternating
direction method of multipliers (ADMM) and analog over-the-air aggregation without channel …

… estimation, feedback quantization, delay in signal acquisition on a fading channel, etc.
can make the updated model received in user devices or coordinator to be inaccurate [35] in …

… local training. In this paper, we consider a bandwidth-limited wireless fading broadcast channel
from … In the digital downlink, the PS employs quantization followed by channel coding to …

… federated learning model while also establishing notation. We also discuss the basics of
over-the-air aggregation based wireless … Federated Learning Model We can formally describe …

… by learning accuracy level, and thus (ii) between the Federated Learning time and UE
energy consumption. We fill this gap by formulating a Federated Learning over wireless network …