2010•International Conference on Computational Problem-SolvingRequires access

Research for adaptive digital predistortion based on BP-LMS

Zhiying Guo, Jingchang Nan, Jiuchao Li

Open publisher page 1 citations

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.

About this research paper

What this paper is about

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.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available 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.

Key concepts: Predistortion, Amplifier, Computer science, Electronic engineering, Convergence (economics), Power (physics), Control theory (sociology), Least mean squares filter

Related papers

Back to paper searchBrowse research topicsOriginal source
Research for adaptive digital predistortion based on BP-LMS — Research Paper | ScholarLens