scholarly journals Nonuniform Overlapping Method in Designing Microstrip Patch Antennas Using Genetic Algorithm Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
J. M. Jeevani W. Jayasinghe ◽  
Jaume Anguera ◽  
Disala N. Uduwawala ◽  
Aurora Andújar
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Optimized Design ◽  
Patch Antennas ◽  
Algorithm Optimization ◽  
Patch Area ◽  
Microstrip Patch Antennas ◽  
Microstrip Patch ◽  
Design Flexibility ◽  
Overlapping Method

Genetic algorithm (GA) has been a popular optimization technique used for performance improvement of microstrip patch antennas (MPAs). When using GA, the patch geometry is optimized by dividing the patch area into small rectangular cells. This has an inherent problem of adjacent cells being connected to each other with infinitesimal connections, which may not be achievable in practice due to fabrication tolerances in chemical etching. As a solution, this paper presents a novel method of dividing the patch area into cells with nonuniform overlaps. The optimized design, which is obtained by using fixed overlap sizes, shows a quad-band performance covering GSM1800, GSM1900, LTE2300, and Bluetooth bands. In contrast, use of nonuniform overlap sizes leads to obtaining a pentaband design covering GSM1800, GSM1900, UMTS, LTE2300, and Bluetooth bandswith fractional bands with of 38% due to the extra design flexibility.

scholarly journals A Machine Learning-Based Approach for Antenna Design Using Class_Reg Algorithm Optimized Using Genetic Algorithm

2021 ◽  
Vol 9 (11) ◽  
pp. 1682-1686
Author(s):  
Suriya Prakash Jambunathan
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Patch Antenna ◽  
Ring Resonator ◽  
Split Ring Resonator ◽  
Simulation Software ◽  
Patch Antennas ◽  
Split Ring ◽  
Microstrip Patch Antennas ◽  
Microstrip Patch

Abstract: Microstrip patch antennas are predominantly in use in mobile communication and healthcare. Their performances are even improved, using Split-Ring Resonator cells. But finding the ideal dimensions of the microstrip patch antenna and calculating the correct number and size of the split ring resonator cells consume a lot of time when we use Electromagnetic Simulation software to design first and then simulate. Using the pre-calculated results of certain sets of microstrip patch antennas with split ring resonators, a machine learning model can be trained and hence be used to predict the antenna metrics when the dimensions are specified. When the machine learning algorithms are combined with feature-optimization algorithms such as the Genetic Algorithm, the efficiency and performance can be improved further. Keywords: Machine Learning, Micro-strip Patch Antenna, Genetic algorithm, Split Ring Resonator.

Bio-Inspired Algorithms Applied on Microstrip Patch Antennas: a Review

2016 ◽  
Vol 6 (6) ◽  
pp. 336
Author(s):  
Omar A. Saraereh ◽  
Amer A. Al Saraira ◽  
Qais H. Alsafasfeh ◽  
Aodeh Arfoa
Keyword(s):  
Patch Antennas ◽  
Microstrip Patch Antennas ◽  
Microstrip Patch

An improved design of harmonic suppression for microstrip patch antennas

2006 ◽  
Vol 49 (1) ◽  
pp. 103-105 ◽  
Author(s):  
M. K. Mandal ◽  
P. Mondal ◽  
S. Sanyal ◽  
A. Chakrabarty
Keyword(s):  
Patch Antennas ◽  
Harmonic Suppression ◽  
Microstrip Patch Antennas ◽  
Microstrip Patch ◽  
Improved Design
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