DocumentCode
1377449
Title
A New Approach to Pruning Volterra Models for Power Amplifiers
Author
Crespo-Cadenas, Carlos ; Reina-Tosina, Javier ; Madero-Ayora, María J. ; Muñoz-Cruzado, Jesús
Author_Institution
Dept. de Teor. de la Serial y Comun., Univ. de Sevilla, Sevilla, Spain
Volume
58
Issue
4
fYear
2010
fDate
4/1/2010 12:00:00 AM
Firstpage
2113
Lastpage
2120
Abstract
The objective of this paper is to present an approach to behavioral modeling that can be applied to predict the nonlinear response of power amplifiers with memory. Starting with the discrete-time, complex-baseband full Volterra model, we define a novel methodology that retains only radial branches that can be implemented with one-dimensional finite impulse response filters. This model is subsequently simplified by selecting a subset of directions using an ad hoc procedure. Both models are evaluated in terms of accuracy in the time and frequency domains and complexity, and are compared with other models described in the literature. The evaluation is conducted using a low-voltage silicon RF driver amplifier and a 5-W PA, which are characterized at different levels with diverse modulation formats, including wideband code-division multiple-access (WCDMA) and orthogonal frequency-division multiplexed (OFDM) signals. In all cases, comparison of the measured and simulated responses confirms the effectiveness of the proposed approach.
Keywords
FIR filters; OFDM modulation; code division multiple access; power amplifiers; OFDM; RF driver amplifier; ad hoc procedure; complex-baseband full Volterra model; diverse modulation formats; one-dimensional finite impulse response filters; orthogonal fre?? quency-division multiplexed signals; power 5 W; power amplifiers; wideband code-division multiple-access; Dynamic behavioral models; Volterra series; memory polynomials; nonlinear identification; power amplifiers;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2009.2039815
Filename
5373869
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