An interactive genetic algorithm approach to MMIC low noise amplifier design using a layered encoding structure

Author

Neoh, Siew Chin ; Marzuki, Arjuna ; Morad, Norhashimah ; Lim, Chee Peng ; Aziz, Zalina Abdul

fYear

2008

fDate

1-6 June 2008

Firstpage

1571

Lastpage

1575

Abstract

In this paper, an interactive genetic algorithm (IGA) approach is developed to optimize design variables for a monolithic microwave integrated circuit (MMIC) low noise amplifier. A layered encoding structure is employed to the problem representation in genetic algorithm to allow human intervention in the circuit design variable tuning process. The MMIC amplifier design is synthesized using the Agilent Advance Design System (ADS), and the IGA is proposed to tune the design variables in order to meet multiple constraints and objectives such as noise figure, current and simulated power gain. The developed IGA is compared with other optimization techniques from ADS. The results showed that the IGA performs better in achieving most of the involved objectives.

Keywords

MMIC amplifiers; encoding; genetic algorithms; integrated circuit design; low noise amplifiers; Agilent Advance Design System; agilent advance design system; circuit design variable tuning process; interactive genetic algorithm; layered encoding structure; monolithic microwave integrated circuit low noise amplifier; noise figure; simulated power gain; Algorithm design and analysis; Design optimization; Encoding; Genetic algorithms; Integrated circuit noise; Low-noise amplifiers; MMICs; Microwave amplifiers; Microwave integrated circuits; Monolithic integrated circuits;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-1822-0

Electronic_ISBN

978-1-4244-1823-7

Type

conf

DOI

10.1109/CEC.2008.4631001

Filename

4631001