A Novel Solution based on Multi-Objective AI Techniques for Optimization of CMOS LC_VCOS

Abstract

A method of optimizing components and transistors sizing for CMOS Cross-Coupled LC voltage controlled oscillators is presented in this paper. The design constrains of power consumption, phase noise, and the Figure of Merit (FoM) of LC_VCOs are applied on Multi-Objective AI techniques, simultaneously. The design parameters of LC_VCOs are obtained from the two strong algorithms, the Multi-Objective Inclined Planes system Optimization (MOIPO) and the Multi-Objective Particle Swarm Optimization (MOPSO). It was  implemented in MATLAB, to the Pareto Optimal Front (POF) solutions, which have an amazingly trade-off between three objective functions. The LC_VCO circuits were simulated using this method in a 0.18μm-CMOS process by HSPICE RF environment. The results show that the size of components of the PMOS-only and NMOS-only integrated LC_VCOs and the optimal trade-off curve between minimum power and minimum phase noise.