Machine Learning for Wireless Communication: Principles and Applications
Edited by Dr. Sanjay Agal
Unlock the future of connectivity where algorithms power intelligent communication systems. Machine Learning for Wireless Communication: Principles and Applications is your essential guide to the transformative synergy between machine learning and next-generation wireless technologies.
Whether you're a researcher, student, or industry professional, this comprehensive volume bridges the gap between theory and practical application. Covering foundational concepts—from supervised and unsupervised learning to deep learning and reinforcement learning—it progresses into real-world applications such as 5G/6G optimization, IoT integration, edge computing, and network security.
With clear explanations, illustrative case studies, and insights from seasoned educators and engineers, this book goes beyond technical depth to offer a strategic vision of how data-driven intelligence is reshaping wireless networks.
Step into a world where machines not only learn but anticipate, adapt, and revolutionize how we connect.
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Dr Sanjay Agal, Deepika Pandey, Dhanya PM, Snehal Thakor, Anju Mahesh
Dr. Sanjay Agal is a dedicated educator, researcher, and academic leader with a passion for innovation in engineering and data science. Currently serving as Professor and Head of the Department of Artificial Intelligence and Data Science at Parul University, Vadodara, India, Dr. Agal brings over two decades of experience in academia and institutional leadership. Prior to this role, he served as Principal of Dr. V.R. Godhania College of Engineering & Technology in Porbandar, where he championed academic excellence and infrastructure development.
Endorsed by Gujarat Technological University (GTU) for the Principal’s position in 2023, Dr. Agal’s career has been distinguished by a commitment to bridging the gap between theoretical foundations and real-world application. His scholarly contributions include the authorship of six books, a wide array of research publications in international journals, and the successful filing of several patents. His work reflects a deep focus on cutting-edge domains such as machine learning, wireless networks, and intelligent systems.
As the editor of Machine Learning for Wireless Communication: Principles and Applications, Dr. Agal brings his extensive expertise to curate a resource that is both academically rigorous and practically insightful. He is committed to equipping students, researchers, and professionals with the knowledge and tools needed to thrive in an increasingly data-driven world.
Driven by a vision to inspire the next generation of technologists, Dr. Agal fosters an academic environment where inquiry, innovation, and collaboration are at the heart of learning. His leadership continues to influence curriculum design, interdisciplinary research, and the cultivation of future-ready professionals.
