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Effects of signal PDF on the identification of behavioral polynomial models for multicarrier RF power amplifiers

机译:信号PDF对多载波RF功率放大器行为多项式模型识别的影响

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This paper proposes an experimental study of the sensitivities of the power amplifier modelling and their influences on the system’s identification. Two memory polynomial models are widely investigated in the behavioural modelling and linearization of RF power amplifiers (PAs). In order to improve the accuracy of the behavioural modeling versus identification, we assess the performances of these models under different signal bandwidths, statistics and signal distributions. For this purpose, normalized mean square error has been used to compare the model output to measured data when the PA is driven under multi-carrier input signals. Measurement results and simulation have been carried out and the results demonstrated the effects of the signal characteristics on the performances of the model. Multi-carrier wideband code-division multiple access and multi-tone signals were used with an experimental Doherty amplifier. The obtained results revealed a degradation of the polynomial model performances when the statistics of the input signals change with similar peak-to-average power ratio.
机译:本文对功率放大器建模的敏感性及其对系统识别的影响进行了实验研究。在射频功率放大器(PA)的行为建模和线性化过程中,广泛研究了两个记忆多项式模型。为了提高行为建模相对于识别的准确性,我们评估了这些模型在不同信号带宽,统计数据和信号分布下的性能。为此,当在多载波输入信号下驱动PA时,已使用归一化均方误差将模型输出与测量数据进行比较。进行了测量结果和仿真,结果表明了信号特性对模型性能的影响。多载波宽带码分多址和多音频信号与实验性Doherty放大器一起使用。当输入信号的统计量以相似的峰均功率比变化时,获得的结果表明多项式模型性能下降。

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