This book examines real-world applications, including mobile communication, the Internet of Things (IoT), and wireless sensor networks, emphasizing practical deployment. It further discusses device-to-device communication protocols, wireless personal area networks, and wireless body area networks. The book highlights opportunities and challenges with experimental software-defined radio networks.
Features:
- Provides an in-depth exploration of the recent technologies in the domain of wireless communication systems and networks.
- Examines real-world applications, including mobile communication, the IoT, and wireless sensor networks and emphasizes practical deployment.
- Addresses key challenges in 5G wireless networks and beyond, like spectrum management and maximizing utilization while minimizing interference.
- Discusses mmWave communication, software-defined radio, cognitive radio networks, and non-orthogonal multiple access (NOMA).
- Explains the concepts of machine learning and deep learning models and how they can be applied in the domain of wireless communication and networks to draw meaningful conclusions.
It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, wireless communications, networking communications, telecommunications, and communications system design.
Budhaditya Bhattacharyya is currently working as Professor at School of Electronics Engineering (SENSE), Vellore Institute of Technology (VIT), Vellore. His current research interests include deep learning-based channel estimation strategies for Next Generation wireless networks and intrusion detection analysis for 5G networks.
Anindita Kundu is an Associate Professor in the Department of Software Systems, School of Computer Science and Engineering, of Vellore Institute of Technology, Vellore. Her current research interests include Robotic Path Planning, Internet of Things and Opportunistic Networks.
Ananthakrishna Chintanpalli is currently a Professor at the Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology (VIT), Vellore. His research interests include signal processing, bio-medical signal processing, auditory modeling to predict speech recognition scores, psychoacoustics, speech processing, and deep neural networks.
Xavier Fernando is a Professor at Toronto Metropolitan University (TMU), Canada. His area of research is application of machine learning and artificial intelligence to resolve various engineering and IoT challenges.
