刘发林
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DOI码:10.1109/TBC.2024.3434625
所属单位:中国科学技术大学信息学院
教研室:电子工程与信息科学系
发表刊物:IEEE Transactions on Broadcasting
项目来源:国家自然科学基金 NSFC 62371436
关键字:Behavioral modeling, basis function screening, digital predistortion (DPD), piecewise model, power amplifiers (PAs), running complexity, segmentation rules.
摘要:This paper proposes a dual feature indexed quadratic polynomial-based piecewise (DIQP) behavioral modeling technique for digital predistortion (DPD) of RF transmitters. The proposed DIQP model is used to find the most suitable DPD model by performing a dual feature classification on the optimized submodels with a reuse-based function screening algorithm. The optimized submodel is adapted from the previous instantaneous sample indexed magnitude-selective affine (I-MSA) function-based model by transforming the original single linear term into a quadratic term with stronger fitting ability. This key improvement not only enhances the flexibility of the model but also boosts its fitting capability. The segmentation rule of the piecewise model has evolved from a simple threshold segmentation to a dual feature segmentation based on threshold and clustering segments. This reconstruction provides the model with enhanced feature-building capabilities. Additionally, the corresponding hybrid basis function screening (HBFS) algorithm and running complexity identification algorithm based on basis function reuse are proposed. The ingenious design of this reuse-based function screening algorithm not only enhances running efficiency but also ensures the overall performance of the model. The experimental part uses two different power amplifiers (PAs) for behavioral modeling and linearization tests. And the results of the experiments prove that the screened DIQP model is able to achieve the linearization performance-complexity trade-off excellently.
合写作者:Renlong Han,Chengye Jiang,Guichen Yang,Qianqian Zhang,Junsen Wang
第一作者:Hao Chang (昌昊)
论文类型:期刊论文
通讯作者:Falin Liu
论文编号:10.1109/TBC.2024.3434625
学科门类:工学
文献类型:J
卷号:70
期号:4
页面范围:1302-1315
是否译文:否
发表时间:2024-12-12
收录刊物:SCI、EI