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Optimizing CMOS LNA circuits through multi-objective meta heuristics

机译:通过多目标元启发式优化CMOS LNA电路

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摘要

Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Recently, the mono-objective version of the PSO algorithm was adapted and used to optimize only one performance of RF circuits, mainly the voltage gain of low noise amplifiers. In this work, we propose to optimize more than one performance function of LNAs while satisfying imposed and inherent constraints. We deal with generating the Pareto front linking two conflicting performances of a LNA, namely the voltage gain and the noise figure. The adopted idea consists of using the symbolic expressions of the scattering parameters ((S21) for the voltage gain, and (S11, S22) for input and output matching). For this purpose we use a Multi-Objective Optimization algorithm PSO incorporating the mechanism of the crowding distance technique (MOPSO-CD). Comparisons with results obtained using NSGA II are presented and ADS simulations, using 0.35µm CMOS technology, are given to show good reached results.
机译:粒子群优化(PSO)已显示是一种有效,坚固且简单的优化算法。最近,PSO算法的单目标版本被调整并用于仅优化RF电路的一个性能,主要是低噪声放大器的电压增益。在这项工作中,我们建议优化LNA的多于一个性能功能,同时满足施加和固有的约束。我们处理产生帕累托前部连接的LNA冲突性能,即电压增益和噪声系数。所采用的思想包括使用散射参数的符号表达式((S21),用于输入和输出匹配的电压增益的(S11,S22))。为此目的,我们使用多目标优化算法PSO结合着拥挤距离技术的机制(MOPSO-CD)。呈现使用NSGA II获得的结果的比较,并使用0.35μmCMOS技术的ADS模拟,以显示出良好的达到结果。

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