Investigating the performance of cross-coupled CMOS LC-VCOs using genetic algorithm

Emad Ebrahimi, S. Naseh
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引用次数: 5

Abstract

A fast simulation-based and parasitic-aware LC-VCO optimizer CAD tool, using Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) is presented. The proposed CAD tool optimizes the power consumption and phase noise of each conventional LC-VCO (e.g. NMOS-only, PMOS-only and complementary), simultaneously. In order to evaluate the fitness of the LC-VCO, the harmonic balance analysis is performed by HSPICE RF and then the optimizer core, implemented in MATLAB, manipulates the fitness and suggests some optimized designs. This CAD tool has the ability to optimize Figure of Merit of each configuration too. Design methodologies and comparison of performance of each structure, based on trade-off curves, are also presented and in a case study the cross-coupled LC-VCOs are optimized for 2.4-GHz central frequency (802.11 IEEE) in a commercial 0.18μm RF-CMOS technology.
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利用遗传算法研究交叉耦合CMOS lc - vco的性能
提出了一种基于精英非支配排序遗传算法(NSGA-II)的基于仿真和寄生感知的LC-VCO优化CAD工具。所提出的CAD工具同时优化了每个传统LC-VCO(例如仅nmos,仅pmos和互补)的功耗和相位噪声。为了评估LC-VCO的适应度,采用HSPICE RF进行谐波平衡分析,然后在MATLAB中实现优化器核心,对适应度进行处理并提出一些优化设计。该CAD工具还具有对各结构的优值图进行优化的能力。本文还介绍了基于权衡曲线的设计方法和每种结构的性能比较,并在一个案例研究中,在商用0.18μm RF-CMOS技术上对交叉耦合lc - vco进行了2.4 ghz中心频率(802.11 IEEE)的优化。
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