Data-Driven Intelligence in Wireless Networks

Concepts, Solutions, and Applications
This book highlights the importance of data-driven techniques to solve wireless communication problems. It presents a number of problems (e.g., related to performance, security, and social networking), and provides solutions using various data-driven techniques, including machine learning, deep learning, federated learning, and AI.

This book highlights the importance of data-driven techniques to solve wireless communication problems. It presents a number of problems (e.g., related to performance, security, and social networking), and provides solutions using various data-driven techniques, including machine learning, deep learning, federated learning, and artificial intelligence.

This book details wireless communication problems that can be solved by data-driven solutions. It presents a generalized approach toward solving problems using specific data-driven techniques. The book also develops a taxonomy of problems according to the type of solution presented and includes several case studies that examine data-driven solutions for issues such as quality of service (QoS) in heterogeneous wireless networks, 5G/6G networks, and security in wireless networks.

The target audience of this book includes professionals, researchers, professors, and students working in the field of networking, communications, machine learning, and related fields.

Contributor: Muhammad Khalil Afzal (Edited by), Muhammad Ateeq (Edited by), Sung Won Kim (Edited by)

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