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AM-AM/AM-PM distortion versus complex Volterra kernels for modeling RF transceiver blocks

机译:AM-AM / AM-PM失真与复杂的Volterra内核用于建模RF收发器块

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We investigate AM/PM distortion models and compare them with baseband (BB) Volterra models. We show that the AM/PM model can be considered a special case of memoryless baseband Volterra models, and that adding memory can improve modeling accuracy by allowing the simulation of more complex nonlinearities. We report models of an LNA, a downconversion mixer, an upconversion mixer, and one class-AB Power Amplifier. All circuits are simulated using the 45nm STMicroelectronics CMOS process with Virtuoso, while the PA, with discrete devices, is simulated using ADS. Adding memory improves performance at the expense of increased numerical complexity: this makes real-time simulation and real-time calibration more expensive, so that there is a trade-off between complexity and accuracy or linearity (after calibration). Foreground calibration's techniques only require the real-time computation of the correction (inverse) system's output, whereas background calibration also requires the real-time estimation of the model coefficients, so the relevant complexity is that which is required during correction.
机译:我们调查AM / PM失真模型,并将它们与基带(BB)Volterra模型进行比较。我们表明AM / PM模型可以被视为内记忆基带Volterra模型的特殊情况,并且添加内存可以通过允许模拟更复杂的非线性来提高建模精度。我们报告LNA,下变频混合器,上变频器和一个类AB功率放大器的模型。使用45nm STMicroelectronics CMOS工艺进行模拟所有电路,使用Virtuoso进行模拟,使用ADS模拟PA。添加内存以增加数值复杂度的费用提高性能:这使得实时仿真和实时校准更昂贵,因此在复杂性和准确度或线性之间存在权衡(校准后)之间存在权衡。前景校准的技术只需要校正(反)系统的输出的实时计算,而背景背景校准也需要模型系数的实时估计,因此相关的复杂性是在校正期间所需的复杂性。

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