DOI码：10.1109/LMWC.2022.3148407

所属单位：中国科学技术大学

教研室：电子工程与信息科学系

发表刊物：IEEE Microwave and Wireless Components Letters

项目来源：国家自然科学基金 61471333

关键字：Behavioral modeling, digital predistortion (DPD), generalized ridge regression (GRR), power amplifiers (PAs).

摘要：Learning from fewer samples can effectively reduce the computational complexity of the parameter identification in digital predistortion (DPD). We refer to this kind of approach as few-sample learning (FSL). However, FSL is always challenging since the ill-conditioning of the matrix will lead to overfitting. In this letter, we explore a stable parameter identification method for FSL DPD based on generalized ridge regression (GRR) and give two closed-form expressions of GRR for fast implementation. Experiments confirm that the proposed method can achieve better performance than the previous methods without any prior knowledge.

合写作者：Wen Qiao,Chengye Jiang,Lei Su

第一作者：Guichen Yang (杨贵晨)

论文类型：期刊论文

通讯作者：Falin Liu

学科门类：工学

文献类型：J

卷号：32

期号：6

页面范围：603-606

是否译文：否

发表时间：2022-06-01

收录刊物：SCI、EI