Particle swarm optimization for dual-band implantable antennas

2007 ◽  
Author(s):  
Aaron Zachary Hood ◽  
Erdem Topsakal
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Dual Band ◽  
Swarm Optimization ◽  
Implantable Antennas

Particle Swarm Optimization Algorithms Applied to Antenna and Microwave Design Problems

2012 ◽  
pp. 100-126
Author(s):  
Sotirios K. Goudos ◽  
Zaharias D. Zaharis ◽  
Konstantinos B. Baltzis
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Dual Band ◽  
Design Problems ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Fitness Sharing ◽  
Microwave Design ◽  
Velocity Mutation

Particle Swarm Optimization (PSO) is an evolutionary optimization algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this chapter, the authors apply different PSO variants to common antenna and microwave design problems. The Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms are applied to real-valued optimization problems. Correspondingly, discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with velocity mutation (BPSO-vm) are used to solve discrete-valued optimization problems. In case of a multi-objective optimization problem, the authors apply two multi-objective PSO variants. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. The design examples presented here include microwave absorber design, linear array synthesis, patch antenna design, and dual-band base station antenna optimization. The conclusion and a discussion on future trends complete the chapter.

scholarly journals Particle Swarm Optimization for Antenna Designs in Engineering Electromagnetics

2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Nanbo Jin ◽  
Yahya Rahmat-Samii
Keyword(s):  
Particle Swarm Optimization ◽  
Patch Antenna ◽  
Ground Plane ◽  
Particle Swarm ◽  
Dual Band ◽  
Radiation Characteristics ◽  
Swarm Optimization ◽  
Multiobjective Problems ◽  
Wave Antenna ◽  
Measurement Results

This paper presents recent advances in applying particle swarm optimization (PSO) to antenna designs in engineering electromagnetics. By linking the PSO kernel with external electromagnetic (EM) analyzers, the algorithm has the flexibility to handle both real and binary variables, as well as multiobjective problems with more than one optimization goal. Three examples, including the designs of a dual-band patch antenna, an artificial ground plane of a surface wave antenna, and an aperiodic antenna array, are presented. Both simulation and measurement results are provided to illustrate the effectiveness of applying the swarm intelligence to design antennas with desired frequency response and radiation characteristics for practical EM applications.

scholarly journals A new technique to design planar dipole antennas by using Bezier curve and Particle Swarm Optimization

2016 ◽  
Vol 65 (3) ◽  
pp. 513-525 ◽  
Author(s):  
Nuttaka Homsup ◽  
Winyou Silabut ◽  
Vuttichai Kesornpatumanum ◽  
Pravit Boonek ◽  
Waroth Kuhirun
Keyword(s):  
Particle Swarm Optimization ◽  
Ieee 802.11 ◽  
Particle Swarm ◽  
New Technique ◽  
Dual Band ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Swarm Optimization ◽  
A New Technique ◽  
5 Ghz

Abstract This research presents a new technique which includes the principle of a Bezier curve and Particle Swarm Optimization (PSO) together, in order to design the planar dipole antenna for the two different targets. This technique can improve the characteristics of the antennas by modifying copper textures on the antennas with a Bezier curve. However, the time to process an algorithm will be increased due to the expansion of the solution space in optimization process. So as to solve this problem, the suitable initial parameters need to be set. Therefore this research initialized parameters with reference antenna parameters (a reference antenna operates on 2.4 GHz for IEEE 802.11 b/g/n WLAN standards) which resulted in the proposed designs, rapidly converted into the goals. The goal of the first design is to reduce the size of the antenna. As a result, the first antenna is reduced in the substrate size from areas of 5850 mm2 to 2987 mm2 (48.93% approximately) and can also operates at 2.4 GHz (2.37 GHz to 2.51 GHz). The antenna with dual band application is presented in the second design. The second antenna is operated at 2.4 GHz (2.40 GHz to 2.49 GHz) and 5 GHz (5.10 GHz to 5.45 GHz) for IEEE 802.11 a/b/g/n WLAN standards.

Particle Swarm Optimization as Applied to Electromagnetic Design Problems

2018 ◽  
Vol 9 (2) ◽  
pp. 47-82 ◽  
Author(s):  
Sotirios K. Goudos ◽  
Zaharias D. Zaharis ◽  
Konstantinos B. Baltzis
Keyword(s):  
Particle Swarm Optimization ◽  
Mobile Communications ◽  
Transfer Functions ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Base Station ◽  
Dual Band ◽  
Design Problems ◽  
Swarm Optimization ◽  
Multi Objective

Particle swarm optimization (PSO) is a swarm intelligence algorithm inspired by the social behavior of birds flocking and fish schooling. Numerous PSO variants have been proposed in the literature for addressing different problem types. In this article, the authors apply different PSO variants to common design problems in electromagnetics. They apply the Inertia Weight PSO (IWPSO), the Constriction Factor PSO (CFPSO), and the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithms to real-valued optimization problems, i.e. microwave absorber design, and linear array synthesis. Moreover, the authors use discrete PSO optimizers such as the binary PSO (binPSO) and the Boolean PSO with a velocity mutation (BPSO-vm) in order to solve discrete-valued optimization problems, i.e. patch antenna design. Additionally, the authors apply and compare binPSO with different transfer functions to thinning array design problems. In the case of a multi-objective optimization problem, they apply two multi-objective PSO variants to dual-band base station antenna optimization for mobile communications. Namely, these are the Multi-Objective PSO (MOPSO) and the Multi-Objective PSO with Fitness Sharing (MOPSO-fs) algorithms. Finally, the authors conclude the paper by providing a discussion on future trends and the conclusion.

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