A Parallel Electromagnetic Genetic-Algorithm Optimization (EGO) Application for Patch Antenna Design

Villegas, F.J.; Cwik, T.; Rahmat‐Samii, Y.; Manteghi, Majid

doi:10.1109/tap.2004.834071

Cited by 149 publications

(59 citation statements)

References 34 publications

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“…Genetic algorithm (GA) is a powerful optimization technique that has been shown to be useful in a wide area of electromagnetics [24][25][26][27][28][29][30][31][32]. GA is applied to design broadband [26,27], multiband [28][29][30] and miniature [31,32] MPAs.…”

Section: Introductionmentioning

confidence: 99%

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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

Jayasinghe¹,

Anguera²,

Uduwawala³

2012

PIER M

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Abstract-Design of multiband antennas with low volume is of practical interest for the ever growing wireless communication industry.In this regard, the design of a small multi band microstrip patch antenna (MPA) for GSM900 (880-960 MHz), GSM1800 (1710-1880 MHz), GSM1900 (1850-1990, UMTS (1920-2170, LTE2300 (2305-2400 MHz), and Bluetooth (2400-2483.5 MHz) applications by using a genetic algorithm (GA) is proposed. The proposed GA method divides the overall patch area into different cells taking into account that cells have a small overlap area between them. This avoids optimized geometries with certain cells having only an infinitesimal connection to the rest of the patch. Therefore, the proposed method is robust for manufacturing. A shorting pin is also included for impedance matching. GA optimization combined with finite element method (FEM) is used to optimize the patch geometry, the feeding position and the shorting position. A prototype has been built showing good agreement with the simulated results. The optimized MPA has a footprint of 46 mm × 57 mm

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Section: Introductionmentioning

confidence: 99%

“…GA is applied to design broadband [26,27], multiband [28][29][30] and miniature [31,32] MPAs. It is a robust, stochastic-based search method, which can handle the common characteristics of electromagnetic optimization problems that are not readily handled by other traditional optimization methods.…”

Section: Introductionmentioning

confidence: 99%

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

Jayasinghe¹,

Anguera²,

Uduwawala³

2012

PIER M

View full text Add to dashboard Cite

show abstract

“…With respect to parametric design techniques (e.g., as in [26,27]), where a reference shape for the antenna structure is a-priori fixed, the proposed method provides flexibility in generating widely different stuctures. On the other hand, with respect to the so-called building-block design technique (e.g., as in [28,29]), where the antenna structure is obtained by properly combining a number of elementary blocks, the proposed approach allows the geometry description by means of a reduced number of parameters. These two aspects are fundamental in order to obtain an effective synthesis procedure.…”

Section: Introductionmentioning

confidence: 99%

A Time-Domain Approach to the Synthesis of Uwb Antenna Systems

Lizzi¹,

Oliveri²,

Massa³

2012

PIER

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Abstract-In this paper, an approach for the synthesis of UltraWideband (UWB) antenna systems in the time domain is proposed.Starting from the definition of suitable time-domain performance indexes, the design process is based on a spline representation of the antenna shape and a Particle Swarm Optimization (PSO) aimed at matching optimal radiation and electrical conditions. The effectiveness of the proposed time-domain technique is assessed by means of both numerical and experimental results.

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“…The GA has been widely used for solving complex electromagnetic (EM) problems [14][15][16][17]. Varied antennas, such as monopole antennas [18,19], Yagi antennas [20,21], patch antennas [22][23][24][25] and array antennas [26][27][28][29] are designed for certain kinds of radiating target by GA optimization.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of Low RCS Patch Antennas Based on a Genetic Algorithm

Zhu¹,

Shao²,

Li³

et al. 2012

PIER

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Abstract-In this article, a genetic algorithm (GA) is employed to the design of low radar cross section (RCS) patch antennas. Combined with the high frequency simulation software (HFSS) for antenna simulations, the GA performs the optimization of geometric parameters.In order to reduce the RCS while holding the satisfying radiation performance of antennas, the radiation model and scattering model are respectively calculated. The combination of proportionate selection and elitist model for the selection strategy is used to speed up the convergence of the GA. Two-point crossover is adopted to accelerate the converging speed and results in more fit individuals. Moreover, the whole design procedure is auto-controlled by programming the VBScript in the HFSS. Two examples of low RCS slot antennas are provided to verify the accuracy and efficiency of the proposed method.

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A Parallel Electromagnetic Genetic-Algorithm Optimization (EGO) Application for Patch Antenna Design

Cited by 149 publications

References 34 publications

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

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

A Time-Domain Approach to the Synthesis of Uwb Antenna Systems

Design and Optimization of Low RCS Patch Antennas Based on a Genetic Algorithm

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