Addressing the communication bottleneck inherent in federated learning (FL), over-the-air
FL (AirFL) has emerged as a promising solution, which is, however, hampered by deep …

We demonstrate that merely analog transmissions and match filtering can realize the
function of an edge server in federated learning (FL). Therefore, a network with massively …

Federated learning (FL) provides a privacy-preserving approach to realizing networked
intelligence. However, the performance of FL is often constrained by the limited …

When implementing hierarchical federated learning over wireless networks, scalability
assurance and the ability to handle both interference and device data heterogeneity are …

Federated edge learning enables intelligence services to be deployed at the edge of future
wireless network. To address the limited spectral resource and constrained scalability …

In recent years, federated learning has been widely studied to speed up various\textit
{supervised} learning tasks at the wireless network edge under communication constraints …