Multi-Objective Hybrid Optimization Algorithm for Design a Printed MIMO Antenna with n78 - 5G NR Frequency Band Applications

This study introduces a novel multi-objective optimization algorithm integrating Customized Mutated Particle Swarm Optimization (CM-PSO) and an innovative modified Genetic Algorithm (GA) using an unexplored merged chaotic map. The hybrid algorithm converges to desired results faster than CM-PSO and...

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Veröffentlicht in:IEEE access Jg. 11; S. 1
Hauptverfasser: Hosseini, Vahid, Farhang, Yousef, Majidzadeh, Kambiz, Ghobadi, Changiz
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Antenna radiation patterns
Antennas
Chaotic Map
CM-PSO Algorithm
Computer simulation
Criteria
Design optimization
Dipole antennas
Frequencies
Genetic Algorithm
Genetic algorithms
Hybrid Optimization Algorithms
Microstrip antennas
MIMO Antennas
Multiple objective analysis
Optimization
Optimization algorithms
Parameter modification
Particle swarm optimization
Printed Antennas
Resonant frequency
Software algorithms
ISSN:2169-3536, 2169-3536
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Zusammenfassung:This study introduces a novel multi-objective optimization algorithm integrating Customized Mutated Particle Swarm Optimization (CM-PSO) and an innovative modified Genetic Algorithm (GA) using an unexplored merged chaotic map. The hybrid algorithm converges to desired results faster than CM-PSO and modified GA without trapping in local minima. Validation is conducted by designing a single-element and simple-structure dipole antenna so that its optimized S 11 is better than -30 dB at the resonance frequency and covers the 3.3 to 3.8 GHz frequency band with S 11 < -10 dB. Certainly, the -30 dB and covering frequency band criteria can be modified in the proposed algorithm. In the algorithm, the isolation between elements of a quad-Multiple-Input/Multiple-Output antenna, constructed using optimized dipole antennas, is set to be less than -20 dB (changeable criteria) so that the smallest size can be achieved. Computer Simulation Technology (CST) Studio Suite carries out electromagnetic and high-frequency simulations, and the novel developed optimization algorithm in MATLAB determines what and how much parameter values need to be changed by CM-PSO or an innovative modified GA in order to enhance the antenna's S 11 result and its Impedance Bandwidth (IBW). The input parameters of the algorithm are the dimensions of the proposed antenna's elements, which significantly influence its performance.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3292307