Modeling, analysis and classification of a PA based on identified Volterra Kernels

Silveira, D. ; Gadringer, M. ; Arthaber, H. ; Mayer, M. ; Magerl, G. (2005) Modeling, analysis and classification of a PA based on identified Volterra Kernels. In: Gallium Arsenide applications symposium. GAAS 2005, 3-7 ottobre 2005, Parigi.
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Abstract

This article presents the modeling of a microwave Power Amplifier (PA)in the almost linear and compression operation modes. An in-band quasi-white noise real-valued signal is used as input for the identification process to excite every possible source of nonlinearity. A segment of the input-out put measurement data is processed to generate an initial Parallel Cascade Wiener Model (PCWM).The model is cross-validated with the entire measurement signal. The first order Volterra kernel is extracted in order to obtain an estimation of the amplifier’s memory. A new model is generated and its Volterra kernels up to the second order are estimated to apply the Structural Classification Methods(SCM). The result of this process is a suitable block-structure for the final amplifier model. The optimized model is intended to be numerically robust having a high identification percentage based on a variance figure of merit. This resulting model can be used for simulation of linearization systems or even in further identification processes.

Abstract
Document type
Conference or Workshop Item (Paper)
Creators
CreatorsAffiliationORCID
Silveira, D.
Gadringer, M.
Arthaber, H.
Mayer, M.
Magerl, G.
Subjects
DOI
Deposit date
15 Feb 2006
Last modified
17 Feb 2016 14:19
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