An optimal selection of classic twobox behavioral models for RF power amplifiers
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摘要: 提出了一种选取射频功率放大器的最优行为模型并获取指纹特征的方法。针对Wiener模型和Hammerstein模型,提出了一种基于加权最小二乘法的最优行为模型选取方法,并给出了具体的数学分析。并对实际系统的功率放大器进行数值仿真,验证了算法的可行性及有效性,即首先根据训练集得到放大器的行为模型系数,再采用多种评判标准,通过分析测试集、训练集的误差得到最优行为模型。数值仿真结果表明:本文提出的方法能够有效地选取射频功率放大器的最优行为模型,且拟合误差较小。
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关键词:
- 射频功率放大器 /
- 行为模型 /
- 指纹特征 /
- Wiener模型 /
- Hammerstein模型
Abstract: This paper presents a method that aims at selecting the optimal behavioral model and figuring out the fingerprint of the RF power amplifiers. First of all, it introduces the main classification of the behavioral models. Then, regarding Wiener model and Hammerstein model, it proposes an algorithm with a detailed mathematical explanation, which is based on weighted least squares method and obtains the optimal behavioral models successfully. Finally, it presents a numerical simulation for RF power amplifiers in the real world and validates the practicability and effectiveness of the algorithm. In the simulation, firstly the parameters of the behavioral models are computed through the training signals, then the optimal behavioral model is selected by analyzing the errors according to various judgment criteria. The result of numerical simulation reflects the algorithm could obtain the optimal behavioral models of the RF power amplifiers effectively with a relatively small error.-
Key words:
- RF power amplifier /
- behavioral model /
- recognition of fingerprint /
- Wiener model /
- Hammerstein model
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