A simplified predistortion linearization scheme for power amplifier with memory
Yeqing Qian, Fuqiang Liu, Yuhui Huang
Abstract
Yeqing Qian, Fuqiang Liu, Yuhui Huang
Abstract
This paper presents a simplified predistortion linearization scheme for power amplifier modelled by Wiener model. According to characteristics of the Hammerstein model and the predistorter, two step simplifications are given to Hammerstein model and a simplified memory nonlinear predistorter (PD) model is achieved. And previously presented high-efficient predistortion structure based on polynomial is extended for the proposed PD model. The predistortion of PA with memory can be greatly simplified using the presented model and the extended predistortion structure. Simulation results demonstrated that the proposed scheme exhibits a fast convergence and good linearization performance.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This paper presents a simplified predistortion linearization scheme for power amplifier modelled by Wiener model. According to characteristics of the Hammerstein model and the predistorter, two step simplifications are given to Hammerstein model and a simplified memory nonlinear predistorter (PD) model is achieved. And previously presented high-efficient predistortion structure based on polynomial is extended for the proposed PD model. The predistortion of PA with memory can be greatly simplified using the presented model and the extended predistortion structure. Simulation results demonstrated that the proposed scheme exhibits a fast convergence and good linearization performance.
Key concepts: Predistortion, Linearization, Amplifier, Control theory (sociology), Convergence (economics), Computer science, Nonlinear system, Power (physics)