2019
DOI: 10.2528/pierc19061602
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A Miniature Rectangular Patch Antenna Using Defected Ground Structure for Wlan Applications

Abstract: The purpose of this work is to miniaturize a rectangular patch antenna which resonates at 2.4 GHz. To achieve this, we present a new geometry of a pi-shaped slot with three annular rings as a Defected Ground Structure (DGS). DGS is a periodic etched structure or aperiodic sequence of configurations, and it has been used to switch the resonance frequency from starting value 13 GHz to an ending value at 2.4 GHz without any changes in the areas of the actual rectangular microstrip patch antenna (RMPA). The propos… Show more

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Cited by 9 publications
(5 citation statements)
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References 15 publications
(15 reference statements)
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“…Table 6 gives a comparison of the final proposed antenna dimensions with published literature. [32][33][34][35][36] A reduction in size has been achieved with our antenna design from 43.49% to 88.58%.…”
Section: Resultsmentioning
confidence: 95%
“…Table 6 gives a comparison of the final proposed antenna dimensions with published literature. [32][33][34][35][36] A reduction in size has been achieved with our antenna design from 43.49% to 88.58%.…”
Section: Resultsmentioning
confidence: 95%
“…Te DGS is noted for its minimal space requirements and straightforward design, achieved by etching a slot in the ground plane of the microstrip circuit. Additionally, Suvarna et al [17] introduces a new pi-shaped DGS with three annular rings which is etched in the ground plane. Furthermore, Ghaloua et al [18] propose the utilization of a new geometric DGS on an FR-4 substrate with a relative permittivity equal to 4.4, a thickness of 1.6 mm, and a loss tangent of 0.025 to downsize the antenna arrays.…”
Section: Defected Ground Structurementioning
confidence: 99%
“…The other parameters, r 1 and r 2 represent the arbitrary values existing from 0 to 1. In (13), w presents the inertia weight that helps in balancing the algorithm's global and local search ability. Here, the fitness value of each particle's position is estimated as per a certain fitness function.…”
Section: Particle Swarm Optimization (Pso)mentioning
confidence: 99%
“…Though, optimal selection of design parameters of MPA such as patch size, substrate thickness, dielectric constant and feeding method, etc., can help achieve to operate over the desired frequency range [10][11][12]. There have been several investigations conducted with such motives; however, retaining stable and controllable performance with optimal trade-offs between dimension and performance has remained a challenge [9] [13]. During the past few years, artificial neural network (ANN) or data-driven machine learning (ML) based approaches have been proposed to estimate a suitable set of design parameters for MPA design.…”
Section: Introductionmentioning
confidence: 99%