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Book Synopsis

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.

DataDriven Intelligence in Wireless Networks

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A Paperback by Muhammad Khalil Afzal

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    View other formats and editions of DataDriven Intelligence in Wireless Networks by Muhammad Khalil Afzal

    Publisher: CRC Press
    Publication Date: 12/19/2024
    ISBN13: 9781032107738, 978-1032107738
    ISBN10: 1032107731

    Description

    Book Synopsis

    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.

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