English

T Wiri Abraham

doi:10.5897/jeeer2018.0621

Abstract

This paper investigates the use of a Genetic Algorithm to produce an optimized compact monopole antenna for textile application. The antenna characteristics are examined using the Numerical Electromagnetic code (NEC2) with genetic algorithm (GA). The design objective for the antennas considered here is to drive the S11 to be less than or at least, as close as possible to -10dB, targeting this application (850-950 MHz) band. Results of return loss are also presented. The purpose of this study is to build a genetic algorithm (GA) optimisation of wire antennas for application at 900MHz. These antennas are fully textile, flexible and wearable. Measurement test was performed by placing the textile antenna sample close to the human chest while results were compared with simulation on a body phantom. Specific absorption rate was evaluated in CST Microwave Studio. To validate our results, four linear wire antenna designs, planar and embroidered antennas were fabricated, measured and compared with the simulation. Simulated and measured results show that all the antennas can operate at 900 MHz band. Key words: Genetic algorithm, linear wire, segment length, population, chromosome, specific absorption rate.

Highlights

Antennas are amongst the most essential components in any wireless system, as they transform a signal that flows through wires into an electromagnetic wave that propagates through free space
Using genetic algorithm (GA) with electromagnetic simulation, antennas are designed based on wire configuration
GA optimization involves randomized operators and many evolutions were reaching for an optimum solution

Summary

Introduction

Antennas are amongst the most essential components in any wireless system, as they transform a signal that flows through wires into an electromagnetic wave that propagates through free space. A good design of the antenna improves the overall system performance aspresentedbyBalanis ( 2 0 1 6 ). Antenna design is performed either empirically or via simulator using numerical method. These are broadly classified into those based on the integral or differential form of Maxwell’s equations. The former typically produces frequency domain solution and the latter time domain. Using genetic algorithm (GA) with electromagnetic simulation, antennas are designed based on wire configuration. Genetic algorithms are used to explore the design domain and automatically discover a novel antenna design that can be more effective than would be developed (Altshuler and Linden, 1997). GAs operates on a population of potential solutions applying the principal of survival of the fittest to produce better and better approximations to a solution (Choi et al, 2015)

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Results

Conclusion