Title :
Blackbox macro-modeling of the nonlinearity based on Volterra series representation of X-parameters
Author :
Xiong, Xiaoyan Y. Z. ; Li Jun Jiang ; Schutt-Aine, Jose E. ; Weng Cho Chew
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China
Abstract :
Volterra series representation is a powerful mathematical model for nonlinear devices. However, the difficulties in determining higher-order Volterra kernels limited its broader applications. This paper proposed a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters for the first time. Then the Vandermonde method is employed to separate different orders of Volterra kernels at the same frequency, which leads to a highly efficient extraction process. The proposed Volterra series representation based on X-parameters is further benchmarked for verification. The proposed new algorithm is very useful for the blackbox macro-modeling of nonlinear devices and systems.
Keywords :
Volterra series; nonlinear network analysis; Vandermonde method; Volterra series representation; X-parameters; blackbox macro-modeling; higher-order Volterra kernels; mathematical model; nonlinear devices; Harmonic analysis; Integrated circuit modeling; Kernel; Numerical models; Scattering parameters; Systematics; Time-domain analysis; Volterra series; X-parameters; macro-modeling;
Conference_Titel :
Electrical Performance of Electronic Packaging and Systems (EPEPS), 2014 IEEE 23rd Conference on
Print_ISBN :
978-1-4799-3641-0
DOI :
10.1109/EPEPS.2014.7103601