Microstrip antenna parameters optimization

Subject Areas : Majlesi Journal of Telecommunication Devices

Zohreh Dorrani ¹ ()

Received: 2015-10-25 Accepted : 2016-01-03 Published : 2016-01-01

Keywords: en,

Abstract :

The genetic algorithm is one of the most powerful optimization algorithms in electromagnetism. In this paper, we optimized gain of a microstrip patch antenna using genetic algorithms. The cavity method used for the analysis of this antenna. The simulation results were compared with results obtained in previous work. The resulting gave gain more than the previous one

References:

[1] N. Chattoraj, G. Sekhar Roy, “Application of Genetic Algorithm to the Optimization of Microstrip Antennas with and without Superstrate,” Mikrotalasna revija, pp.32-35, Novembar 2006.

[2] Da-G. Fang, “Antenna Theory and Microstrip Antennas,” CRC Press, 1 edition, pp. 20-35. 2009.

[3] R. Garg, Bhartia. P, Bahl. I and Ittipiboon. A, "Microstrip Antenna Design Handbook," Artech House, 2001.

[4] IJ Bahl, P. Bhartia, and SS Stuchly, “Design of a Microstrip Antenna Covered with a Dielectric Layer,” IEEE Trans. Antennas & Propagation, Vol. AP-30, pp. 314-318, March 1980.

[5] JM Johnson and Y. Rahmat-Samii, “Genetic algorithms in engineering electromagnetics,” IEEE Antennas and Propagation Magazine, vol. 39, no. 4, pp. 7-21, 1997.

[6] RL Haupt, “Introduction to genetic algorithms for electromagnetics,” IEEE Antennas and agation Magazine, vol. 37, no. 2, pp. 7-15, 1995.

[7] DE Goldberg, “Genetic Algorithms, Addison-Wesley,” 1989.

[8] WJM Jeevani, etal, “Nonuniform Overlapping Method in Designing Microstrip patch Antennas Using Genetic Algorithm Optimization,” International Journal of Antennas and Propagation, vol 2015.pp01-8, 2015.

[9] S. Jayaprakasam, KA R Sharul and Y. Chee Leow, “Paretoo elite selection genetic algorithm forrandom antenna array beamforming with low sdelobe level,” Progress In Electromagnetics Research B, Vol. 51,