R. Kanthavel - Artificial Intelligent Techniques for Wireless Communication and Networking

Scrivener Publishing
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Artificial Intelligence and So Computing for Industrial Transformation

Series Editor: Dr. S. Balamurugan ()

Scope: Artificial Intelligence and So Computing Techniques play an impeccable role in industrial transformation. The topics to be covered in this book series include Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithms, Particle Swarm Optimization, Evolutionary Algorithms, Nature Inspired Algorithms, Simulated Annealing, Metaheuristics, Cuckoo Search, Firey Optimization, Bio-inspired Algorithms, Ant Colony Optimization, Heuristic Search Techniques, Reinforcement Learning, Inductive Learning, Statistical Learning, Supervised and Unsupervised Learning, Association Learning and Clustering, Reasoning, Support Vector Machine, Dierential Evolution Algorithms, Expert Systems, Neuro Fuzzy Hybrid Systems, Genetic Neuro Hybrid Systems, Genetic Fuzzy Hybrid Systems and other Hybridized So Computing Techniques and their applications for Industrial Transformation. The book series is aimed to provide comprehensive handbooks and reference books for the benefit of scientists, research scholars, students and industry professional working towards next generation industrial transformation.

Publishers at Scrivener
Martin Scrivener ()
Phillip Carmical ()

Edited by

R. Kanthavel

K. Ananthajothi

S. Balamurugan

R. Karthik Ganesh

This edition first published 2022 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 978-1-119-82127-4

Cover image: Pixabay.Com

Cover design by Russell Richardson

Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

Printed in the USA

10 9 8 7 6 5 4 3 2 1

In the current digital era, artificial intelligence (AI) resembling human intelligence is enabling superior inventions for the advancement of the world. Broadening the scientific scope of AI has made it possible to change fundamentals and modulate everlasting facts in the wireless communication and networking domains. This breakthrough in AI miraculously preserves the inspired vision of communication technology.

Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is also elaborated. Moreover, the application side of integrated technologies are also explored to enhance AI Revolution innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments.

This book allows both practitioners and researchers to share their opinions and recent research on the convergence of these technologies with those in academia and industry. The contributors have presented their technical evaluation and comparative analysis of existing technologies; and theoretical explanations and experimental case studies related to real-time scenarios are also included. Furthermore, this book will connect IT professionals, researchers, and academicians working on 5G communication and networking technologies.

The book is organized into 20 chapters that address AI principles and techniques used in wireless communication and networking. It outlines the benefits, functions, and future role of AI in wireless communication and networking. In addition, AI applications are addressed from a variety of aspects, including basic principles and prominent methodologies that offer researchers relevant instructions to follow in their research. The editing team and expert reviewers in various disciplines have thoroughly reviewed the information included.

• In , Comprehensive and Self-Contained Introduction to Deep Reinforcement Learning, P. Anbalagan, S. Saravanan and R. Saminathan present a brief guide to the deep reinforcement learning process and its detailed applications and research directions in order to enhance the basics of reinforcement mechanisms.
• In , Impact of AI in 5G Wireless Technologies and Communication Systems, A. Sivasundari and K. Ananthajothi present an in-depth overview of the implementation of AI to improve 5G wireless communication systems, discuss the role and difficulties faced, and highlight suggestions for future studies on integrating advanced AI into 5G wireless communications.
• In , Artificial Intelligence Revolution in Logistics and Supply Chain Management, P.J. Satish Kumar, Ratna Kamala Petla, Elangovan K and P.G. Kuppusamy give a brief description of recent developments and some relevant impacts concerning logistics and supply chain related to AI.
• In , An Empirical Study of Crop Yield Prediction Using Reinforcement Learning, M. P. Vaishnnave and R. Manivannan use reinforcement learning (RL) data technologies and high-performance computing to create new possibilities to activate, calculate, and recognize the agricultural crop forecast.