Author Description

<p>This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and elaborates discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems which are important in intelligent wireless communications.</p> <p>Features:</p> <ul> <li>Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications.</li> <li>Presents high speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks.</li> <li>Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks.</li> <li>Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning.</li> <li>Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection, and sparse channel estimation.</li> </ul> <p>It is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.</p>