Journal
IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS
Volume 30, Issue 12, Pages 1117-1120Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LMWC.2020.3027878
Keywords
Matching pursuit algorithms; Mathematical model; Bayes methods; Reactive power; Cost function; Estimation; Microwave theory and techniques; Bayesian information criterion (BIC); digital predistortion (DPD); doubly orthogonal matching pursuit (DOMP); hill climbing (HC) algorithm; order reduction; power amplifier (PA)
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Funding
- Spanish National Board of Scientific and Technological Research [TEC2017-82807-P]
- European Regional Development Fund (ERDF) of the European Commission
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This work presents insights on the application of the Bayesian information criterion (BIC) to fix the optimum number of coefficients in the Volterra series applied to the modeling and linearization of power amplifiers (PAs). The BIC is transformed from a rule to be applied after selection techniques to a stopping criterion, which enables the halting of the algorithm when a condition is reached. This study reveals that the BIC is equivalent to allow a certain identification normalized mean square error (NMSE) decrease after the inclusion of a model component. Experimental results of the digital predistortion of a class J PA are provided, demonstrating the proposal applicability in the attaining of the optimum number of coefficients. A comparison is made between the results obtained when the stopping rule is applied to the hill climbing (HC) and the doubly orthogonal matching pursuit (DOMP) algorithms.
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