A Novel 20G Wide-Band Synthesis Methodology for CMOS Spiral Inductors using Neural Network and Genetic Algorithm

Abstract

We develop a novel synthesis way to effectively generate CMOS spiral inductor’s layout parameters using artificial neural network and genetic algorithm. An accurate neural network model for CMOS spiral inductors is firstly developed based on measured results from TSMC 0.13um MM/RF process with the frequency range of 1-20 GHz. The neural network model is further integrated in the synthesis simulator kits called SPUNK. An innovative synthesis technique is then applied in which genetic algorithm based optimization is adopted. Our methodology promises to provide greater accuracy than previous results in the frequency range while able to minimize the time cost for spiral inductor design.