A new augmented support vector regression‐based behavioral model for multi‐device power amplifiers
A new augmented support vector regression‐based behavioral model for multi‐device power amplifiers
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DOI：
10.1002/mop.32630
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发表时间：
2020-09
影响因子：
1.5
通讯作者：
Jialin Cai;J. King;Jiangtao Su;Chao Yu;Shichang Chen;Lingling Sun;Jun Liu
中科院分区：
文献类型：
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作者：
Jialin Cai;J. King;Jiangtao Su;Chao Yu;Shichang Chen;Lingling Sun;Jun Liu
提出了一种基于增广时延支持向量回归(SVR)的多器件射频非线性功率放大器(PA)行为模型。给出了所提出的建模技术的原理，以及详细的建模步骤。实验结果表明，与基本SVR模型和现有的增强SVR(ASVR)模型相比，新的增广SVR(NASVR)模型的性能有了显著的提高。当应用于多器件Doherty功放时，模型预测值与测量数据之间的归一化均方误差为44.4d B，分别比基本−模型和现有的svr模型改善了9d B和4.5d B以上。
A new behavioral model based on augmented time‐delay support vector regression (SVR) for multi‐device radio frequency (RF) nonlinear power amplifiers (PAs), is proposed in this paper. The theory of the proposed modeling technique is provided, along with a detailed modeling procedure. Experimental results show that the proposed new augmented SVR (NASVR) model leads to significant performance improvements when compared with basic SVR models and existing Augmented SVR (ASVR) models. When applied to a multi‐device Doherty PA, a normalized mean square error (NMSE) between model prediction and measurement data of −44.4 dB is obtained, representing a more than 9 and 4.5 dB improvement compared with the basic SVR model and the existing ASVR model, respectively.