Title :
Research for adaptive digital predistortion based on BP-LMS
Author :
Guo, Zhiying ; Nan, Jingchang ; Li, Jiuchao
Author_Institution :
Liaoning Tech. Univ., Huludao, China
Abstract :
In general, the characteristic of the radio frequency power amplifier varies with many kinds of factors, such as the environment temperature, power supply, etc. In order to guarantee the steady operation of the predistortion power amplifier, the adaptive performance of the predistortion system seems very important. Based on the original adaptive algorithm, this paper presents a new variable step size LMS algorithm based on neural network (BP_LMS) for the shortcoming convergence performance of the standard LMS algorithm, and applied it to adaptive digital predistortion. Finally, it build an adaptive predistortion system in MATLAB, simulation results show that the algorithm in improved predistortion amplifier is better than previous algorithms.
Keywords :
adaptive signal processing; mathematics computing; neural nets; power amplifiers; radiofrequency amplifiers; MATLAB; adaptive digital predistortion; least mean square algorithm; neural network; predistortion amplifier; radio frequency power amplifier; standard LMS algorithm; step size LMS algorithm; Adaptation model; Convergence; Least squares approximation; Mathematical model; Predistortion; Signal processing algorithms;
Conference_Titel :
Computational Problem-Solving (ICCP), 2010 International Conference on
Conference_Location :
Lijiang
Print_ISBN :
978-1-4244-8654-0