Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems

Author:

Demircioglu Erdem1,Yagli Ahmet Fazil1,Gulgonul Senol1,Ankishan Haydar2,Tartan Emre Oner2,Sazli Murat H.3,Imeci Taha4

Affiliation:

1. Turksat International Satellite Cable TV Operator, Golbasi, 06380 Ankara, Turkey

2. Baskent University, Technical Science MYO, Baglica, 06810 Ankara, Turkey

3. Electrics and Electronics Department, Ankara University, Golbasi, 06380 Ankara, Turkey

4. Electrical and Electronics Engineering Department, Istanbul Commerce University, Kucukyali, 34840 Istanbul, Turkey

Abstract

This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs) using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN). To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN’s conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering

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