A modified broadband weighted magnitude‐selective behavioral model for digital predistortion of radio frequency power amplifiers. Issue 7 (4th April 2022)

• Record Type: Journal Article
• Authors: Yao, Tingting; He, Songbai; Peng, Jun; You, Fei; Zhang, Hu
• Is Part Of: International journal of RF and microwave computer-aided engineering. Volume 32:Issue 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-04
• Subjects: affine function -- behavioral modeling -- broadband -- digital predistortion -- weighted memory polynomial; Microwave devices -- Computer-aided design -- Periodicals; Computer-aided engineering -- Periodicals; 621.3813
• DOI: 10.1002/mmce.23182
• Languages: English
• ISSNs: 1096-4290

Abstract

Abstract: With the increasing demand for large signal bandwidth in communication systems, the complexity of the behavioral model of power amplifier (PA) will also increase. In this paper, a modified weighted magnitude‐selective model based on magnitude‐selective affine (MSA) function based model and weighted memory polynomial model is proposed to ensure low complexity and good modeling performance under broadband signal excitation. This model is constructed by using the power‐dependent weighted function instead of the sum of multiple MSA functions in MSA. It can not only be used to solve the nonlinearity of PA excited by large bandwidth signal but also reducing the model coefficients without affecting the modeling performance makes the digital predistortion of large bandwidth signals more simple and effective. In this paper, a 100 MHz broadband signal is used for simulation and experiment on a wideband PA. The results show that for the same performance the WMA model required approximately 80% less coefficients.