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Título:
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Comparison of model order reduction techniques for digital predistortion of power amplifiers
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Autor/a:
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Gilabert Pinal, Pere Lluís; Montoro López, Gabriel; Wang, Teng; Ruiz, Nieves; García García, José Ángel
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. CSC - Components and Systems for Communications Research Group |
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Abstract:
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©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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Abstract:
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This paper compares and discusses four
techniques for model order reduction based on compressed
sensing (CS), less relevant basis removal (LRBR), principal
component analysis (PCA) and partial least squares (PLS). CS
and PCA have already been used for reducing the order of power
amplifier (PA) behavioral models for digital predistortion (DPD)
purposes. While PLS, despite being popular in some signal
processing areas, to the best author’s knowledge, still has not
been used in the PA linearization field. Finally, the LRBR is an
iterative search algorithm proposed by the authors in this paper
for the sake of comparison. Experimental results are presented
and the advantages and drawbacks of each method discussed. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Enginyeria electrònica::Electrònica de potència
-Power amplifiers
-Compressed sensing
-Digital predistortion
-Partial least squares
-Power
-Amplifier
-Principal component analysis
-Amplificadors de potència |
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Derechos:
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Tipo de documento:
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Artículo - Versión presentada
Objeto de conferencia |
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Editor:
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Institute of Electrical and Electronics Engineers (IEEE)
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