Multi-Section Support Vector Regression-Based Behavioral Modeling of RF GaN Doherty Power Amplifiers

被引：3
|
作者：
Qi, Lin [1 ]
Yin, Hang [1 ]
Chen, Peng [1 ]
Cai, Jialin [3 ]
Zhu, Xiao-Wei [1 ]
Yu, Chao [1 ,2 ]
Hong, Wei [1 ,2 ]
机构：
[1] Southeast Univ, State Key Lab Millimeter Waves, Nanjing, Peoples R China
[2] Purple Mt Lab, Nanjing, Peoples R China
[3] Hangzhou Dianzi Univ, Key Lab RF Circuit & Syst, Hangzhou, Peoples R China
来源：
2021 IEEE MTT-S INTERNATIONAL WIRELESS SYMPOSIUM (IWS 2021) | 2021年
基金：
中国国家自然科学基金;
关键词：
Behavioral model; GaN; support vector regression; power amplifier;
D O I：
10.1109/IWS52775.2021.9499388
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 novel behavioral model based on multi-section support vector regression (MS-SVR) of radio frequency (RF) Gallium Nitride (GaN) Doherty power amplifiers (PAs) is proposed in this paper. In this method, the input signal is divided into different sections according to signal amplitude and each section is modeled separately using SVR. Experimental validation is performed using a 2.4 GHz Doherty PA. The results show that the proposed model can effectively reduce the time of parameter extraction and signal processing.
引用
收藏
页数：3
相关论文
共 50 条
  • [21] Modified small-signal behavioral model for GaN HEMTs based on support vector regression
    Geng, MingQiang
    Cai, Jialin
    King, Justin
    You, Bin
    Su, Jiangtao
    Liu, Jun
    Sun, Lingling
    Cao, Wenhui
    Pan, Mian
    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, 2021, 31 (09)
  • [22] Boosted Model Tree-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifiers
    Li, Yue
    Wang, Xiaoyu
    Pang, Jingzhou
    Zhu, Anding
    IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2021, 69 (09) : 3976 - 3988
  • [23] Dynamic behavioral modeling of RF power amplifiers based on decomposed piecewise machine learning technique
    Cai, Jialin
    King, Justin B.
    Yu, Chao
    Pan, Baicao
    Sun, Lingling
    Liu, Jun
    INTERNATIONAL JOURNAL OF MICROWAVE AND WIRELESS TECHNOLOGIES, 2021, 13 (04) : 315 - 321
  • [24] Support Vector Regression-Based Short-Term Wind Power Prediction With False Neighbours Filtered
    Zhu, L.
    Wu, Q. H.
    Li, M. S.
    Jiang, L.
    Smith, J. S.
    2013 INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATIONS (ICRERA), 2013, : 740 - 744
  • [25] A support vector regression-based interval power flow prediction method for distribution networks with DGs integration
    Liang, Xiaorui
    Zhang, Huaying
    Liu, Qian
    Liu, Zijun
    Liu, Huicong
    Frontiers in Energy Research, 2024, 12
  • [26] Reliable comparison for power amplifiers nonlinear behavioral modeling based on regression trees and random forest
    Aguila-Torres, Daniel Santiago
    Alejandro Galaviz-Aguilar, Jose
    Ricardo Cardenas-Valdez, Jose
    2022 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 22), 2022, : 1527 - 1530
  • [27] Simplified Volterra series based behavioral modeling of RF power amplifiers using deviation-reduction
    Zhu, Anding
    Dooley, John
    Brazil, Thomas J.
    2006 IEEE MTT-S INTERNATIONAL MICROWAVE SYMPOSIUM DIGEST, VOLS 1-5, 2006, : 1113 - +
  • [28] A new accurate volterra-based model for behavioral modeling and digital predistortion of RF power amplifiers
    Du, T. (dutianjiao@bupt.edu.cn), 1600, Electromagnetics Academy (29):
  • [29] RF power amplifiers behavioral modeling based on extended neural network with additional dynamic fuzzy weights
    Yuan, X. -H.
    Feng, Q. -Y.
    Zhou, L. -C.
    JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS, 2013, 27 (13) : 1694 - 1701
  • [30] BEHAVIORAL MODELING OF GaN-BASED POWER AMPLIFIERS: IMPACT OF ELECTROTHERMAL FEEDBACK ON THE MODEL ACCURACY AND IDENTIFICATION
    Quaglia, Roberto
    Camarchia, Vittorio
    Cappelluti, Federica
    Guerrieri, Simona Donati
    Lima, Eduardo G.
    Ghione, Giovanni
    Pirola, Marco
    MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, 2009, 51 (11) : 2789 - 2792
12345