Multi-Objective-Based Approach to Optimize the Analog Electrical Behavior of GSDG MOSFET: Application to Nanoscale Circuit Design

Abstract

In this chapter, the small signal parameters behavior of Gate Stack Double Gate (GSDG) MOSFET are studied and optimized using multi-objective genetic algorithms (MOGAs) for nanoscale CMOS analog circuits’ applications. The transconductance and the OFF-current are the small signal parameters which have been determined by the analytical explicit expressions in saturation and subthreshold regions. According to the analytical models, the objectives functions, which are the pre-requisite of genetic algorithms, are formulated to search the optimal small signal parameters in order to obtain the best electrical and dimensional transistor parameters to obtain and explore the better transistor performances for analog CMOS-based circuit applications. Thus, the encouraging obtained results may be of interest to practical applications. The optimized design is incorporated into circuit simulator to study and show the impact of our approach on the nanoscale CMOS-based circuits design. In this context, we proposed to study the electrical behavior of a ring oscillator circuit. In this study a great improvement of the oscillation frequency has been recorded in our case. The main advantages of the proposed approach are its simplicity of implementation and provide to designer optimal solutions that suites best analog application.