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SYSTEMS AND METHODS OF LINEAR IMPAIRMENT MODELLING TO IMPROVE DIGITAL PRE-DISTORTION ADAPTATION PERFORMANCE

机译:用于改善数字预失真自适应性能的线性损伤建模的系统和方法

摘要

Example embodiment of the systems and methods of linear impairment modeling to improve digital pre-distortion adaptation performance includes a DPD module (610) that is modified during each sample by a DPD adaptation engine (620). A linear impairment modeling module (660) separates the linear and non-linear errors introduced in a power amplifier. The linear impairment model is adjusted during each sample using inputs from the input signal and from an FB post processing module (630). The linear impairment modeling module (660) removes the linear errors, such that the DPD adaptation engine (620) only adapts the DPD module (610) based on the non-linear errors. This increases system stability and allows for the correction of IQ imbalance inside the linear impairment modeling, simplifying the feedback post-processing.
机译:线性损伤建模以改善数字预失真自适应性能的系统和方法的示例实施例包括DPD模块(610),该DPD模块在每个样本期间由DPD自适应引擎(620)修改。线性损伤建模模块(660)分离功率放大器中引入的线性和非线性误差。使用来自输入信号和来自FB后处理模块的输入(630),在每个采样期间调整线性损伤模型。线性损伤建模模块(660)去除线性误差,使得DPD适配引擎(620)仅基于非线性误差适配DPD模块(610)。这增加了系统稳定性,并允许校正线性损伤建模中的IQ不平衡,从而简化了反馈后处理。

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