Federated Learning Over Wireless Edge Networks

In the realm of modern technology, this insightful work explores the intricacies of Federated Learning (FL) within the context of wireless edge networks. Through a comprehensive tutorial approach, the authors unravel the principles of FL, shedding light on its significance in enhancing Edge Intelligence. Readers are guided through the fundamental concepts that underpin FL, emphasizing its potential to empower decentralized data processing and machine learning at the network's edge.

The narrative goes beyond theory, delving into practical applications and challenges associated with implementing FL in real-world scenarios. By addressing critical issues such as communication efficiency and privacy preservation, the authors serve as invaluable guides, offering both researchers and industry practitioners a deeper understanding of how to effectively leverage FL in dynamic wireless environments.