Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier
In this paper, a dynamic behavioral model for digital predistortion (DPD) of RF power amplifier (PA) based on amplitude and phase augmented time-delay twin support vector regression (AP-TSVR) is proposed. Unlike other SVR-based methods, the TSVR model finds a pair of non-parallel planes by solving t...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8708185/ |
| _version_ | 1818914541295108096 |
|---|---|
| author | Jin Xu Weiliang Jiang Linhua Ma Mingyu Li Zhiqiang Yu Zhen Geng |
| author_facet | Jin Xu Weiliang Jiang Linhua Ma Mingyu Li Zhiqiang Yu Zhen Geng |
| author_sort | Jin Xu |
| collection | DOAJ |
| description | In this paper, a dynamic behavioral model for digital predistortion (DPD) of RF power amplifier (PA) based on amplitude and phase augmented time-delay twin support vector regression (AP-TSVR) is proposed. Unlike other SVR-based methods, the TSVR model finds a pair of non-parallel planes by solving two related support vector machine (SVM) type problems, namely, the $\varepsilon $ -insensitive up- and down-bound functions. Furthermore, in order to accelerate the training process, an effective linear regression algorithm was used to solve the paired quadratic programming problems (QPPs) of the TSVR model involved. The simulation results show that the proposed model is able to give improved modeling and distortion mitigation capability than the traditional memory polynomial-based model, and reduce CPU training time than the ordinary SVR model, even when the effects of both nonlinear characteristics and memory effects of PA are considered. To verify the effectiveness of the proposed method, experimental verification was performed using single-device gallium nitride (GaN) PA and GaN Doherty PA, respectively. The experimental results show that the new modeling approach can provide very efficient and extremely accurate linearization performance with improving generalization ability. |
| first_indexed | 2024-12-19T23:48:01Z |
| format | Article |
| id | doaj.art-d61a2e995c0346eeae4b0aab3977ac3e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T23:48:01Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d61a2e995c0346eeae4b0aab3977ac3e2022-12-21T20:01:15ZengIEEEIEEE Access2169-35362019-01-017598325984310.1109/ACCESS.2019.29152818708185Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power AmplifierJin Xu0Weiliang Jiang1Linhua Ma2Mingyu Li3https://orcid.org/0000-0002-9893-3284Zhiqiang Yu4Zhen Geng5School of Aeronautics Engineering, Air Force Engineering University, Xi’an, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing, ChinaInstitute of Unmanned Systems Technology, Northwestern Polytechnical University, Xi’an, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing, ChinaIn this paper, a dynamic behavioral model for digital predistortion (DPD) of RF power amplifier (PA) based on amplitude and phase augmented time-delay twin support vector regression (AP-TSVR) is proposed. Unlike other SVR-based methods, the TSVR model finds a pair of non-parallel planes by solving two related support vector machine (SVM) type problems, namely, the $\varepsilon $ -insensitive up- and down-bound functions. Furthermore, in order to accelerate the training process, an effective linear regression algorithm was used to solve the paired quadratic programming problems (QPPs) of the TSVR model involved. The simulation results show that the proposed model is able to give improved modeling and distortion mitigation capability than the traditional memory polynomial-based model, and reduce CPU training time than the ordinary SVR model, even when the effects of both nonlinear characteristics and memory effects of PA are considered. To verify the effectiveness of the proposed method, experimental verification was performed using single-device gallium nitride (GaN) PA and GaN Doherty PA, respectively. The experimental results show that the new modeling approach can provide very efficient and extremely accurate linearization performance with improving generalization ability.https://ieeexplore.ieee.org/document/8708185/Digital predistortion (DPD)radio frequency (RF) power amplifier (PA)twin support vector regression (TSVR)dynamic behavioral modeling |
| spellingShingle | Jin Xu Weiliang Jiang Linhua Ma Mingyu Li Zhiqiang Yu Zhen Geng Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier IEEE Access Digital predistortion (DPD) radio frequency (RF) power amplifier (PA) twin support vector regression (TSVR) dynamic behavioral modeling |
| title | Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier |
| title_full | Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier |
| title_fullStr | Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier |
| title_full_unstemmed | Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier |
| title_short | Augmented Time-Delay Twin Support Vector Regression-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifier |
| title_sort | augmented time delay twin support vector regression based behavioral modeling for digital predistortion of rf power amplifier |
| topic | Digital predistortion (DPD) radio frequency (RF) power amplifier (PA) twin support vector regression (TSVR) dynamic behavioral modeling |
| url | https://ieeexplore.ieee.org/document/8708185/ |
| work_keys_str_mv | AT jinxu augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier AT weiliangjiang augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier AT linhuama augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier AT mingyuli augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier AT zhiqiangyu augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier AT zhengeng augmentedtimedelaytwinsupportvectorregressionbasedbehavioralmodelingfordigitalpredistortionofrfpoweramplifier |