Anantha Krishna Chintanpalli – författare

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.

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.