Title :
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
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;
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
DOI :
10.1109/CEC.2008.4631001
