{"title":"A novel sparse behavioral model design method based on the global representative point selection and the randomized SVD algorithm","authors":"","doi":"10.1016/j.aeue.2024.155432","DOIUrl":null,"url":null,"abstract":"<div><p>Digital pre-distortion (DPD) technology is currently the dominant technology employed to compensate for the nonlinearity of power amplifiers (PAs). Recently, PA modeling methods based on machine learning have attracted much attention. However, the traditional model still suffers from the defects of long modeling time or insufficiently high modeling accuracy. To solve this problem, the global representative point selection (GRPS) algorithm and the randomized SVD (RSVD) algorithm based on the least squares twin support vector regression (LSTSVR) model are introduced. The GRPS algorithm is first used to select a specific number of globally representative points from all the data to construct the support vector set. Then the RSVD algorithm is used to perform a low-rank approximation to the target kernel matrix. The modeling performance of the proposed approach is compared with the existing model using different communication signals, and the results show that the proposed model can improve the modeling accuracy and reduce the modeling time. Further, a pre-distortion experimental platform is established, and the proposed model is used to pre-distort the Class F PA and the Doherty PA respectively, which proves that the proposed model has a good nonlinear correction effect.</p></div>","PeriodicalId":50844,"journal":{"name":"Aeu-International Journal of Electronics and Communications","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aeu-International Journal of Electronics and Communications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1434841124003182","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Digital pre-distortion (DPD) technology is currently the dominant technology employed to compensate for the nonlinearity of power amplifiers (PAs). Recently, PA modeling methods based on machine learning have attracted much attention. However, the traditional model still suffers from the defects of long modeling time or insufficiently high modeling accuracy. To solve this problem, the global representative point selection (GRPS) algorithm and the randomized SVD (RSVD) algorithm based on the least squares twin support vector regression (LSTSVR) model are introduced. The GRPS algorithm is first used to select a specific number of globally representative points from all the data to construct the support vector set. Then the RSVD algorithm is used to perform a low-rank approximation to the target kernel matrix. The modeling performance of the proposed approach is compared with the existing model using different communication signals, and the results show that the proposed model can improve the modeling accuracy and reduce the modeling time. Further, a pre-distortion experimental platform is established, and the proposed model is used to pre-distort the Class F PA and the Doherty PA respectively, which proves that the proposed model has a good nonlinear correction effect.
期刊介绍:
AEÜ is an international scientific journal which publishes both original works and invited tutorials. The journal''s scope covers all aspects of theory and design of circuits, systems and devices for electronics, signal processing, and communication, including:
signal and system theory, digital signal processing
network theory and circuit design
information theory, communication theory and techniques, modulation, source and channel coding
switching theory and techniques, communication protocols
optical communications
microwave theory and techniques, radar, sonar
antennas, wave propagation
AEÜ publishes full papers and letters with very short turn around time but a high standard review process. Review cycles are typically finished within twelve weeks by application of modern electronic communication facilities.