Title :
Experimental sensitivity analysis of multi-standard power amplifiers nonlinear characterization under modulated signals
Author :
Ben Ayed, Mounir ; Boumaiza, Slim
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
This paper proposes an experimental analysis focusing on the sensitivity of three behavioral models, Memory Polynomial (MP), Augmented Hammerstein (AH) and the two hidden layers artificial neural networks (2HLANN) to the characteristics of the input signal driving the power amplifier (PA) to be linearized. The analysis is carried out by changing separately each signal characteristic, respectively the peak to average power ratio (PAPR), the Probability density function (PDF), and the modulation bandwidth and assess the sensitivity of the DPD to that change. When used to linearise a 250 Watt peak-envelop-power Doherty PA, the considered models showed relatively small sensitivity to the variation of these signal characteristics. Yet, the 2HLANN was found to be the most robust model with excellent linearization capabilities.
Keywords :
nonlinear network analysis; power amplifiers; sensitivity analysis; augmented Hammerstein; experimental sensitivity analysis; hidden layers artificial neural networks; memory polynomial; modulated signals; modulation bandwidth; multistandard power amplifiers nonlinear characterization; peak to average power ratio; probability density function; Bandwidth; Chirp modulation; Peak to average power ratio; Polynomials; Power amplifiers; Power system modeling; Robustness; Sensitivity analysis; Signal analysis; Wireless communication;
Conference_Titel :
Microwave Measurements Conference (ARFTG), 2010 75th ARFTG
Conference_Location :
Anaheim, CA
Print_ISBN :
978-1-4244-6364-0
DOI :
10.1109/ARFTG.2010.5496318