使用进化优化的自下而上的LNAs系统设计方法

C. Sánchez-López, R. Castro-López, E. Roca, F. Fernández, R. Gonzalez-Echevarria, J. Esteban-Muller, J. López-Villegas, J. Sieiro, N. Vidal
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引用次数: 8

摘要

介绍了一种系统的低噪声放大器设计方法。该方法遵循自下而上的方法,采用多目标进化优化算法,该算法在两个层面上使用。首先,利用该方法建立了基于pareto的集成平面电感器性能模型。为此,将考虑电感器布局的电磁模拟器与优化器耦合在一起,从而提供高度精确的性能评估。与代工厂提供的电感库不同,这些基于pareto的模型提供了电感,质量因子和面积之间权衡的详细见解。然后将电感器的基于Pareto的模型用作设计变量来生成LNA Pareto曲面,从而提供高度精确的LNA性能权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A bottom-up approach to the systematic design of LNAs using evolutionary optimization
A systematic design methodology for low-noise amplifiers (LNAs) is introduced. This methodology follows a bottom-up approach that employs a multi-objective evolutionary optimization algorithm, which is used at two levels. First, it is used to generate Pareto-based performance models for integrated planar inductors. To do so, an electromagnetic simulator that takes into account the inductor's layout, thus providing highly accurate performance evaluations, is coupled to the optimizer. Unlike foundry-provided inductor libraries, these Pareto-based models offer a detailed insight of the trade-offs between inductance, quality factor and area. Afterwards the Pareto-based models for the inductors are used as design variables to generate the LNA Pareto surface, thus providing highly accurate performance trade-offs of the LNA.
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