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Elitist Nondominated Sorting Genetic Algorithm Based RF IC Optimizer

机译:基于Elitist非支配排序遗传算法的RF IC优化器

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摘要

An optimization tool for radio frequency integrated circuits (RFICs) based on an elitist nondominated sorting genetic algorithm is introduced. It casts RF circuit synthesis as a multi-objective optimization problem and produces multiple solutions along the Pareto optimal front. Optimization is followed by sensitivity assessment wherein Monte Carlo simulations are performed for the Pareto points with respect to process, voltage, and temperature variations. The tool is validated in the synthesis of a 5.2-GHz direct-conversion receiver front-end that includes a common-gate differential low-noise amplifier, I/Q down-conversion mixers, and a quadrature voltage-controlled oscillator in a 250-nm SiGe BiCMOS process.
机译:介绍了一种基于精英非支配排序遗传算法的射频集成电路(RFIC)优化工具。它将射频电路综合视为多目标优化问题,并沿着帕累托最优前沿产生了多个解决方案。优化之后进行灵敏度评估,其中针对过程,电压和温度变化对帕累托点执行蒙特卡罗模拟。该工具在5.2 GHz直接转换接收机前端的综合中得到了验证,该前端包括一个共栅差分低噪声放大器,I / Q下变频混频器和一个250-MHz正交电压控制振荡器。纳米SiGe BiCMOS工艺。

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