Application of linearization modeling technology for nonlinear RF power devices

Lin, Maoliu, Hua, Xiaojie, Sun, Hongjian and Jiang, Jing (2007) Application of linearization modeling technology for nonlinear RF power devices. In: TENCON 2007 - 2007 IEEE Region 10 Conference, 30th October - 2nd November 2007, Taipei, Taiwan.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/TENCON.2007.4428933

Abstract

Based on nonlinear large-signal scattering functions theory and harmonic superposition principle, we describe a novel method to linearize the scattering function in a form that is similar with classical scatter parameter when considering the influence of the conjugate term of incident signal. Moreover, in case of weakly nonlinear device, combining phase normalization and linearization technique, we analyze the expression of linearized scattering function in polar coordinates and predict the characters of the track of reflected waves. Further examination of these characters, we prove that they are derived from the emergence of conjugate term. To testify the linearization model, we apply this linearization model technique for modeling high electron mobility transistor (HEMT) on large signal network analyzer platform. Finally, after contrasting the linearization model with classical scatter parameter model for the measurements data, we conclude with the efficiency of the model for modeling RF devices.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Radio frequency, Scattering parameters, HEMTs, Signal analysis, Equations, MODFETs, Frequency estimation, Jacobian matrices, Transmitters, Sun
Subjects: H600 Electronic and Electrical Engineering
H800 Chemical, Process and Energy Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Paul Burns
Date Deposited: 14 Feb 2019 18:02
Last Modified: 10 Oct 2019 23:46
URI: http://nrl.northumbria.ac.uk/id/eprint/38020

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics