Support Vector Regression Based Behavioral Model for Load Mismatched PAs

被引：0
|
作者：
Cai, Jialin [1 ]
Yu, Chao [2 ]
Xia, Jing [3 ]
Sun, Lingling [1 ]
Chen, Shichang [1 ]
Pan, Baicao [1 ]
Su, Jiangtao [1 ]
Liu, Jun [1 ]
机构：
[1] Hangzhou Dianzi Univ, Minist Educ, Key Lab RF Circuit & Syst, Hangzhou, Peoples R China
[2] Southeast Univ, State Key Lab Millimeter Wave, Nanjing, Peoples R China
[3] Jiangsu Univ, Sch Comp Sci & Commun Engn, Zhenjiang, Jiangsu, Peoples R China
来源：
2019 IEEE INTERNATIONAL SYMPOSIUM ON RADIO-FREQUENCY INTEGRATION TECHNOLOGY (RFIT2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/rfit.2019.8929153
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A new double-input double-output (DIDO) power amplifier (PA) behavioral model, which takes into account output load termination mismatches, is presented in this paper. The support vector regression (SVR) methodology, from the field of machine learning, is utilized to build this new model. The model is intended for the system-level simulation of amplifier chains subjected to wideband modulated signals. It is validated by comparing the predicted and measured data of a 15 W Gallium Nitride (GaN) based PA under a wide range of voltage standing wave ratios (VSWR). Compared with the conventional memory polynomial (MP) based DIDO models, the obtained results from the new model demonstrate the improved prediction capabilities.
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页数：3
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