A SIMPLE DESIGN OF MULTI BAND MICROSTRIP PATCH ANTENNAS ROBUST TO FABRICATION TOLERANCES FOR GSM, UMTS, LTE, AND BLUETOOTH APPLICATIONS BY USING GENETIC ALGORITHM OPTIMIZATION

2012 ◽  
Vol 27 ◽  
pp. 255-269 ◽  
Author(s):  
Jeevani Windhya Jayasinghe ◽  
Jaume Anguera ◽  
Disala N. Uduwawala
Keyword(s):  
Genetic Algorithm ◽  
Patch Antennas ◽  
Simple Design ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Microstrip Patch Antennas ◽  
Microstrip Patch ◽  
Fabrication Tolerances ◽  
Multi Band

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 GENETIC ALGORITHM OPTIMIZATION FOR MICROSTRIP PATCH ANTENNA MINIATURIZATION

2016 ◽  
Vol 60 ◽  
pp. 113-120 ◽  
Author(s):  
Mohammed Lamsalli ◽  
Abdelouahab El Hamichi ◽  
Mohamed Boussouis ◽  
Naima Amar Touhami ◽  
Tajeddin Elhamadi
Keyword(s):  
Genetic Algorithm ◽  
Patch Antenna ◽  
Microstrip Patch Antenna ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Microstrip Patch ◽  
Antenna Miniaturization

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.

scholarly journals Design of Dual Band Patch Antennas for Cellular Communications by Genetic Algorithm Optimization

2012 ◽  
Vol 1 (1) ◽  
pp. 26 ◽  
Author(s):  
Jeevani Jayasinghe ◽  
Disala Uduwawala ◽  
Jaume Anguera
Keyword(s):  
Genetic Algorithm ◽  
Practical Interest ◽  
Dual Band ◽  
Center Frequency ◽  
Patch Antennas ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
Rectangular Patch ◽  
Shorting Pin ◽  
Final Design

Designing multiband antennas with low volume becomes of practical interest for mobile telecommunications. This paper presents the designs of five small dual band patch antennas for GSM 1800 (1710-1880MHz) and Bluetooth (2400-2483.5MHz) applications using a genetic algorithm combined with MoM (Method of Moments). A substrate with dielectric constant 3.2 and height 8mm is used for the first two dual band designs. The height is reduced thanks to the optimization process to 6mm in the third design by inserting a shorting pin to the fragmented patch antenna. Further the height is reduced to 4mm in the by inserting two shorting pins. In the final design with three shorting pins, the height is only 3mm. The patch dimensions are similar to that of the conventional rectangular patch for the center frequency of the lowest frequency band but with the advantage of having dual-band operation at the desired bands. Genetic algorithm optimization is used to optimize the patch geometry, feed position and shorting positions. HFSS is used to carry out simulations. The antenna thickness is reduced from 8mm to 3mm by incorporating shorting pins which position is optimized by the genetic algorithm.

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