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A Glimpse Beyond 5G in Wireless Networks
Author: Mohammad Abdul Matin
language: en
Publisher: Springer Nature
Release Date: 2022-11-30
This book gathers the latest research findings on emerging trends in 5G and beyond wireless systems. The authors present and assess different enabling technologies, capabilities, and anticipated communications and computing solutions for 5G and beyond. Topics discussed include new frequency bands, new multiple antenna systems, massive D2D connectivity, new network deployment, and more. These discussions help the readers to understand more advanced research materials for developing new ideas to make a contribution in this field for themselves. This book aims to serve as a virtual and effective bridge between academic research in theory and engineering development in practice. Students, professional, and practitioners who seek to learn the latest development in wireless technologies should find interest in this book.
Cognitive Radio Oriented Wireless Networks
This book constitutes the thoroughly refereed conference proceedings of the 11th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2016, held in Grenoble, France, May 30 – April 1, 2016. The 62 revised full papers presented were carefully reviewed and selected from numerous submissions and cover the evolution of cognitive radio technology pertaining to 5G networks. The papers are clustered to topics on dynamic spectrum access/management, networking protocols for CR, modeling and theory, HW architecture and implementations, next generation of cognitive networks, standards and business models, emerging applications for cognitive networks.
TinyML for Edge Intelligence in IoT and LPWAN Networks
Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. - This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. - The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. - Applications from the healthcare and industrial sectors are presented. - Guidance on the design of applications and the selection of appropriate technologies is provided.