Peter Ho Chiung Ching – författare

The scarcity of radio spectrum is one of the most urgent issues at the forefront of future network research that is yet to be addressed. To address the problem of spectrum usage efficiency, the cognitive radio (CR) concept was proposed. The challenges of employing CRs include ensuring secure device operations and data transmission with advanced computing techniques. Successful development of CR systems will involve attainment of the following key objectives: Increasing the rate and capacity of CR-based networks How the power is utilized in CR hardware devices with CMOS circuits How the framework is needed in complex networks Vedic multipliers on CR networks Spatial analysis and clustering methods for traffic management To transmit a large volume of data like video compression Swarm optimization algorithms Resource sharing in peer-to-peer networkingThis book gathers the latest research works focusing on the issues, challenges, and solutions in the field of Cognitive Radio Networks, with various techniques. The chapters in this book will give solutions to the problems that Industry 4.0 faces, and will be an essential resource for scholars in all areas of the field.

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems.The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications.The book is written as a reference that offers the latest technologies and research results to various industry problems.

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems.The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications.The book is written as a reference that offers the latest technologies and research results to various industry problems.