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

Authors

  • Ali Mohammadi
  • Mohammad Mohammadi
  • Seyed Hamid Zahiri

Keywords:

Artificial intelligence techniques, cross-coupled LC_VCOs, Multi-Objective Inclined Planes system Optimization (MOIPO), Multi-Objective Particle Swarm Optimization (MOPSO)

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.

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How to Cite

Mohammadi, A., Mohammadi, M., & Zahiri, S. H. (2016). A Novel Solution based on Multi-Objective AI Techniques for Optimization of CMOS LC_VCOS. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 7(2), 137–144. Retrieved from https://jtec.utem.edu.my/jtec/article/view/625

Issue

Vol. 7 No. 2

Section

Articles

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