Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …

Cognitive radio offers the promise of intelligent radios that can learn from and adapt to their
environment. To date, most cognitive radio research has focused on policy-based radios that …

Despite the growing interest in the interplay of machine learning and optimization, existing
contributions remain scattered across the research board, and a comprehensive overview …

End-to-end learning of communications systems is a fascinating novel concept that has so
far only been validated by simulations for block-based transmissions. It allows learning of …

Narrowband Internet of Things (NB-IoT) is a new technology being implemented into the
Long-Term Evolution (LTE) standards to support machine-to-machine communications …

Does Federated Learning (FL) work when both uplink and downlink communications have
errors? How much communication noise can FL handle and what is its impact on the …

In distributed optimization and machine learning, multiple nodes coordinate to solve large
problems. To do this, the nodes need to compress important algorithm information to bits so …

Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …

Given the unprecedented availability of data and computing resources, there is widespread
renewed interest in applying data-driven machine learning methods to problems for which …

In this paper, the problem of audio semantic communication over wireless networks is
investigated. In the considered model, wireless edge devices transmit large-sized audio …