Research for adaptive digital predistortion based on BP-LMS
Zhiying Guo, Jingchang Nan, Jiuchao Li
Abstract
Zhiying Guo, Jingchang Nan, Jiuchao Li
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.
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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.
Key concepts: Predistortion, Amplifier, Computer science, Electronic engineering, Convergence (economics), Power (physics), Control theory (sociology), Least mean squares filter