Nonlinear Transistor Model Parameter Extraction Techniques

Achieve accurate and reliable parameter extraction using this complete survey of state-of-the-art techniques and methods. A team of experts from industry and academia provides you with insights into a range of key topics, including parasitics, intrinsic extraction, statistics, extraction uncertainty, nonlinear and DC parameters, self-heating and traps, noise, and package effects. Learn how similar approaches to parameter extraction can be applied to different technologies. A variety of real-world industrial examples and measurement results show you how the theories and methods presented can be used in practice. Whether you use transistor models for evaluation of device processing and you need to understand the methods behind the models you use, or you want to develop models for existing and new device types, this is your complete guide to parameter extraction.

Matthias Rudolph is the Ulrich-L.-Rohde Professor for RF and Microwave Techniques at Brandenburg University of Technology, Cottbus, Germany. Prior to this, he worked at the Ferdinand-Braun-Institut, Leibniz Institut für Höchstfrequenztechnik (FBH), Berlin, where he was responsible for modeling of GaN HEMTs and GaAs HBTs and heading the low-noise components group.

Christian Fager is an Associate Professor at Chalmers University of Technology, Sweden, where he leads a research group focusing on energy efficient transmitters and power amplifiers for future wireless applications. In 2002 he received the Best Student Paper Award at the IEEE International Microwave Symposium for his research on uncertainties in transistor small signal models.

David E. Root is Agilent Research Fellow and Measurement and Modeling Sciences Architect at Agilent Technologies, Inc., where he works on nonlinear device and behavioral modeling, large-signal simulation, and nonlinear measurements for new technical capabilities and business opportunities. He is a Fellow of the IEEE and in 2007 he received the 2007 IEEE ARFTG Technology Award.