Nonlinear Modeling Analysis and Predistortion Algorithm Research of Radio Frequency Power Amplifiers - Hardcover

Nan, Jingchang; Gao, Mingming

Hardcover

ISBN 10: 1032010266 ISBN 13: 9781032010267

Publisher: CRC Press, 2021

Synopsis

This book is a summary of a series of achievements made by the authors and colleagues in the areas of radio frequency power amplifier modeling (including neural Volterra series modeling, neural network modeling, X-parameter modeling), nonlinear analysis methods, and power amplifier predistortion technology over the past 10 years.

The book is organized into ten chapters, which respectively describe an overview of research of power amplifier behavioral models and predistortion technology, nonlinear characteristics of power amplifiers, power amplifier behavioral models and the basis of nonlinear analysis, an overview of power amplifier predistortion, Volterra series modeling of power amplifiers, power amplifier modeling based on neural networks, power amplifier modeling with X-parameters, the modeling of other power amplifiers, nonlinear circuit analysis methods, and predistortion algorithms and applications.

Blending theory with analysis, this book will provide researchers and RF/microwave engineering students with a valuable resource.

About this title

About the Author

Jingchang Nan is Professor and doctoral supervisor at Liaoning Technical University. He is also a senior visiting scholar at the University of Michigan. His research interests include RF circuit and systems, communication signal processing and electromagnetic and information processing.

Mingming Gao is Associate Professor and the Vice President of the School of Electronic and Information Engineering, Liaoning Technical University. Her research interests focus on communication engineering, intelligent RF technology, RF circuits and systems, electromagnetic compatibility, linearization technology of power amplifiers and artificial intelligence among other topics.

Edition details

• Publisher: CRC Press
• Publication date: 2021
• Language: English
• ISBN 10: 1032010266
• ISBN 13: 9781032010267
• Binding: Hardcover
• Edition number: 1
• Number of pages: 378