Communication and computation are often viewed as separate tasks. This approach is very
effective from the perspective of engineering as isolated optimizations can be performed …

To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Parallel wireless digital communication with ultralow power consumption is critical for
emerging edge technologies such as 5G and Internet of Things. However, the physical …

The development of applications based on artificial intelligence and implemented over
wireless networks is increasingly rapidly and is expected to grow dramatically in the future …

The concept of hierarchical federated edge learning (H-FEEL) has been recently proposed
as an enhancement of federated learning model. Such a system generally consists of three …

Federated learning (FL) has recently emerged as a promising technology to enable artificial
intelligence (AI) at the network edge, where distributed mobile devices collaboratively train a …

In this paper, we develop an orthogonal frequency-division multiplexing (OFDM)-based over-
the-air (OTA) aggregation solution for wireless federated learning (FL). In particular, the local …

Most works on federated learning (FL) focus on the most common frequentist formulation of
learning whereby the goal is minimizing the global empirical loss. Frequentist learning …

Federated edge learning is a promising technology to deploy intelligence at the edge of
wireless networks in a privacy-preserving manner. Under such a setting, multiple clients …

Federated edge learning is envisioned as the bedrock of enabling intelligence in next-
generation wireless networks, but the limited spectral resources often constrain its …