Guest Editorial Distributed Signal Processing for Edge Learning in B5G IoT Networks

The papers in this special section focus on distributed signal processing for edge learning (EL). EL is a new and promising technology for implementing artificial intelligence (AI) algorithms at edge devices over wireless networks. With the explosive growth in global data traffic, the number of edge devices such as mobile edge computing (MEC), satellite networks, and the Internet-ofthings (IoT) devices increase rapidly. Machine learning (ML) techniques, including deep learning (DL), federated learning (FL), and reinforcement learning (RL), are effective approaches to improve the performance and efficiency of edge networks.