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This paper presents a study oriented at reducing the
computational complexity of least squares (LS) identification of
the parameters describing power amplifier’s (PA) behavioral
models. To reduce the dimensions of the input data matrix, two
strategies are proposed: i) model order reduction based on the
principal component analysis (PCA) theory; and ii) apply a meshselecting
method to reduce the number of required equations. In
this context, the effect of using under-sampling ADCs for the LS
parameter extraction aiming at reducing the costs of PA
identification is also discussed. Finally, the trade-off between the
cost/complexity reduction and quality (or identification accuracy)
loss is evaluated. The proposed strategies can also be considered
for low-computational cost digital predistortion implementations.
CitationWang, T., Gilabert, Pere L., Montoro, G. Under-sampling effects and computational cost reduction in RF power amplifier Behavioral Modeling. A: European Microwave Conference in European Microware Week. "2015 10th European Microwave Integrated Circuits Conference proceedings". Paris: European Microwave Association (EuMA), 2015, p. 57-60.
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