DOI码：10.1109/TMTT.2023.3239794

所属单位：中国科学技术大学电子工程与信息科学系

发表刊物：IEEE Transactions on Microwave Theory and Techniques

项目来源：国家自然科学基金

关键字：Behavioral modeling, digital predistortion (DPD), greedy algorithm, heuristic algorithm, power amplifiers (PAs), pruned basis space (PBS), running complexity.

摘要：A novel behavioral modeling technique called pruned basis space search (PBSS) is proposed for digital predistortion (DPD) of RF power amplifiers (PAs). The PBSS finds the optimal DPD model by basis function search in the pruned basis space (PBS). The PBS is obtained by sparsifying the basis space comprising a wide variety of basis functions, while the basis function search is implemented based on heuristic algorithms. A basis function multiplexing-based complexity identification algorithm is proposed to improve the fitness calculation so that the basis function search can balance the performance and running complexity of the behavioral model. The PBSS model avoids the shortcomings of traditional truncated models and various popular Volterra series-based behavioral modeling approaches and thus offers superior performance. The experimental part performs behavioral modeling and linearization tests on two different PAs. The experimental results confirm that the PBSS model can achieve a better tradeoff between linearization performance and complexity than the state-of-the-art Volterra series-based model.

合写作者：Chengye Jiang,Guichen Yang,Jingchao Tan

第一作者：Renlong Han (韩仁龙)

论文类型：期刊论文

通讯作者：Falin Liu

论文编号：10.1109/TMTT.2023.3239794

学科门类：工学

文献类型：J

卷号：71

期号：7

页面范围：2946-2957

是否译文：否

发表时间：2023-07-01

收录刊物：SCI、EI