Scrivener Publishing
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Beverly, MA 01915-6106
Publishers at Scrivener
Martin Scrivener (martin@scrivenerpublishing.com)
Phillip Carmical (pcarmical@scrivenerpublishing.com)
Edited by
Krishna Kant Singh
KIET Group of Institutions, Delhi-NCR, Ghaziabad, India
Akansha Singh
Department of CSE, ASET, Amity University Uttar Pradesh, Noida, India
Korhan Cengiz
Electrical-Electronics Engineering Department, Trakya University, Edirne, Turkey
and
Dac-Nhuong Le
Faculty of Information Technology, Haiphong University, Vietnam
This edition first published 2020 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-64036-3
Cover image: Pixabay.Com
Cover design by Russell Richardson
The rapid advancements that have recently taken place in communication and network technology have resulted in numerous information services and applications being developed globally. These technological advances continue to have a high impact on society by affecting the way we lead our lives, and although they have undoubtedly improved quality of service and user experience, there is still much to be done. With that in mind, our main objective in writing this book is to address the many challenges associated with this technology and to provide a platform for machine learning-en-abled mobile communications and wireless networks.
Since it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication, in addition to providing mathematical and conceptual background on the latest technology, various areas still needing improvement are discussed in this book, including seamless wide-area coverage, high-capacity hotspots, low-power massive connections, and low-latency and high-reliability wireless networks. In addition to mobile communications and wireless networks, machine-learning techniques are also discussed, including machine-learning architecture and framework, deep reinforcement learning for wireless networks, machine learning–based security and privacy protection for communications/networks, spectrum-aware mobile computing, wireless technology in the Internet of Things (IoT), infrastructure in mobile opportunistic networks, and spectrum allocation in cognitive radio.
Machine learning and cognitive computing have converged to provide some groundbreaking solutions for smart machines. With these two technologies coming together, machines can acquire the ability to reason similar to the human brain. Since the research area of machine learning and cognitive computing covers many fields that can be used effectively for topology management, such as psychology, biology, signal processing, physics, information theory, mathematics, and statistics, the utilization of machine-learning techniques like data analytics and cognitive power will lead to a better performance of communication and wireless systems.
Based on the dominance of the emergent field of machine learning and cognitive computing as applied to mobile communications and wireless networks and the aforementioned facts, this book is an essential guide for all academicians, researchers, and those working in industry in the related field. Because it is an amalgamation of theory, mathematics, and examples of the discussed technologies, this book will also be relevant to all levels of students—from undergraduate and postgraduate to research students— studying computer science or electronics.