Design of an Optimized Micro-Strip Patch Antennausing Meta-Heuristic Algorithms
Palniladevi P1, Kalai Amutha K2, Janani Priya P3

1Palniladevi*, Assistant Professor, ECE Department, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.
2Kalai Amutha, UG Student ECE Department, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.
3Janani Priya, UG student ECE department, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.

Manuscript received on September 15, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 3490-3494 | Volume-8 Issue-12, October 2019. | Retrieval Number: L26131081219/2019©BEIESP | DOI: 10.35940/ijitee.L2613.1081219
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Abstract: In this article, an optimized micro-strip patch antenna for vehicular communication is presented. It consists of rectangular radiating element with 50 Ω microstrip line feed. The FR-4 dielectric material is used as the substrate with relative permittivity of 4.4. ANSYS High Frequency Structure Simulator (HFSS) based on the Finite Element Method (FEM) is used to analyze the performance of the micro-strip patch antenna. Results show that the antenna operated at 5.9 GHz with return loss of -14.07 dB and Voltage Standing Wave Ratio (VSWR) of 1.13. The optimization of the antenna is carried out by employing the meta-heuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). PSO is implemented with the help of MATLAB and GA is performed by ANSYS optimetrics tool. After applying the optimization algorithms, performance of the antenna has been improved. The return loss and VSWR obtained from GA are -34 dB and 1.0 whereas from PSO are -20 dB and 1.65. On comparing GA and PSO, the results obtained from GA are better than PSO. The design methodology of micro-strip patch antenna and the employed optimization techniques are presented.
Keywords: Genetic Algorithm (GA), meta-heuristic, Optimization, Particle Swarm Optimization (PSO)
Scope of the Article: Algorithm Engineering