Optimizing an LNA
Hojat Jafari1, Hossein Ghayoumi Zadeh2, Majid Baghaei-Nejad3, Javad Haddadnia4
1. M.Sc Student In Electrical Engineering, Electrical Engineering Department , Hakim Sabzevari University, Khorasan Razavi, Iran
2. Ph.D Student in Biomedical Engineering, Biomedical Engineering Department, Hakim Sabzevari University, Khorasan Razavi,Iran
3. Assistant Professor OF Electrical Engineering, Electrical Engineering Department ,Hakim Sabzevari University, Khorasan Razavi, Iran
4. Associate Professor of Biomedical Engineering, Biomedical Engineering Department ,Hakim Sabzevari University , Khorasan Razavi, Iran
Corresponding author: email@example.com, Tel +98-910-2911161
Abstract: In this paper, a multi-objective genetic algorithm is provided to help designing electronic circuits. The used optimization algorithm is an extended multi-objective genetic algorithm based on the distributed Pareto frontier, which optimizes circuit parameters in order to achieve low noise, low power and circuit stability. The circuit studied in this paper is a LNA circuit. The genetic algorithm is implemented in MATLAB and circuit simulations are performed using HSPICE and .18 um CMOS technology so that with the two linked software applications, the optimization process is begun. An important feature of this paper is the use of accurate models for the elements in simulation and obtaining results which are very close to reality. The performed simulations indicate that the proposed algorithm has better convergence and diversity in determining optimum solutions compared to multi-objective genetic algorithm NSGA-2. The proposed algorithm converges to the near optimum and optimum solutions with higher efficiency and speed and also enjoys appropriate diversity. Based on the results obtained, GA is shown to be capable in assisting circuit designs, solving the crucial circuit parameters for achieving the required specifications, preference and constraints.
[Hojat Jafari, Hossein Ghayoumi Zadeh, Majid Baghaei-Nejad, Javad Haddadnia. Optimizing an LNA Circuit by Combining Multi-Objective Genetic Algorithm and HSPICE. Life Sci J 2013;10(1):853-859]. (ISSN: 1097-8135). http://www.lifesciencesite.com.
Keywords: LNA; Multi-Objective Genetic Algorithm; optimization.