Ultrawideband Optimized Profile Monopole Antenna by Means of Simulated Annealing Algorithm and the Finite Element Method

Martínez-Fernández, J.; Gil, J.M.; Zapata, J.

doi:10.1109/tap.2007.898593

Cited by 39 publications

(19 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The finite element method 1 (FEM) is an appealing numerical method for its geometrical versatility and robutness, but its CPU time reduces its attraction whenever dense meshing and high frequency resolution over a wide band are required. However, two-dimensional (2-D) FEM analysis can reduce its rather time-consuming characteristics and makes it compatible with CAD [33]. Moreover, some threedimensional (3-D) FEM strategies can be taken into account and make certain CAD possible [32].…”

Section: Introductionmentioning

confidence: 99%

Reliable Fast Frequency Sweep for Microwave Devices via the Reduced-Basis Method

Rubia

Razafison

Maday

2009

IEEE Trans. Microwave Theory Techn.

View full text Add to dashboard Cite

In this paper, a reduced basis approximation-based model order reduction for fast and reliable frequency sweep in the time-harmonic Maxwell's equations is detailed. Contrary to what one may expect by observing the frequency response of different microwave circuits, the electromagnetic field within these devices does not drastically vary as frequency changes in a band of interest. Thus, instead of using computationally inefficient, large dimension, numerical approximations such as finite element or boundary element methods for each frequency in the band, the point in here is to approximate the dynamics of the electromagnetic field itself as frequency changes. A much lower dimension, reduced basis approximation sorts this problem out. Not only rapid frequency evaluation of the reduced order model is carried out within this approach, but also special emphasis is placed on a fast determination of the error measure for each frequency in the band of interest. This certifies the accurate response of the reduced order model. The same scheme allows us, in an offline stage, to adaptively select the basis functions in the reduced basis approximation and automatically select the model order reduction process whenever a preestablished accuracy is required throughout the band of interest. Finally, real-life applications will illustrate the capabilities of this approach.

show abstract

Section: Introductionmentioning

confidence: 99%

Reliable Fast Frequency Sweep for Microwave Devices via the Reduced-Basis Method

Rubia

Razafison

Maday

2009

IEEE Trans. Microwave Theory Techn.

View full text Add to dashboard Cite

show abstract

“…The antenna design space in mobile applications is usually limited; thus, designing a multiband antenna with satisfactory performances is challenging. To reduce the design complexity, several optimization techniques have been applied to wideband or multiband antenna design . However, the literature only straightforwardly applied various optimizers such as genetic algorithms (GAs), particle swarm optimization (PSO), simulated annealing (SA), or invasive weed optimization (IWO) to a design instance at hand, but the nature of the problem of multiband antenna design has not yet been sufficiently clarified.…”

Section: Introductionmentioning

confidence: 99%

“…A successful antenna optimization relies on a proper objective function that guides an optimizer to a promising solution sub‐domain. In general, conventional optimization methods for multiband antenna design apply either the maximum | S 11 ( f )| over sample frequency f or the sum of | S 11 ( f )| in decibel over sample frequency as the objective function to be minimized. The first objective function, namely, max(| S 11 ( f )|), is motivated by searching for a safe performance; that is, because the worst | S 11 ( f )| improves iteration by iteration, a wide and multiband performance should be obtained.…”

Section: Introductionmentioning

confidence: 99%

Performance enhancement of multiband antennas through a two-stage optimization technique

Chen

2016

Int. J. RF Microw. Comput. Aided Eng.

View full text Add to dashboard Cite

This paper presents an optimization technique that aims at multiband antenna design. The proposed method is based on the framework of multi‐objective evolutionary algorithms, and a two‐stage mechanism that balances the degree of optimizing impedance matching and the degree of providing a wide impedance bandwidth is incorporated. Conventionally, the design optimization of multiband antennas relies on minimizing the maximum reflection coefficient or maximizing the area under the return‐loss curve over targeted frequency bands. However, these widely used methods direct an optimization algorithm to improper solution sub‐domains in the multiband design problem. To overcome the limitation of these conventional methods, the general rule of objective functions is thoroughly investigated in this paper. Furthermore, a two‐stage optimizer is designed based on what the multiband optimization problem needs. With the use of the proposed method, two multiband antennas for mobile communication systems covering 824–960 MHz and 1710–2170 MHz are successfully developed. Simulated and measured results show that the proposed technique outperforms conventional optimization approaches significantly.

show abstract

“…Therefore, analytical methods are not applicable any more. Several classical methodologies for the phased-array control have been proposed aimed at defining suitable strategies for the optimal synthesis of antenna arrays [4][5][6][7]. It was shown in [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] that the evolutional optimization algorithms such as the genetic algorithm, ant colony optimization, particle swarm optimization and colony selection algorithm are capable of performing better and more flexible solutions than the classical optimization algorithms and the conventional analytical approaches.…”

Section: Introductionmentioning

confidence: 99%

An Improved Particle Swarm Optimization Algorithm for Pattern Synthesis of Phased Arrays

Li¹,

Shi²,

Hei³

2008

PIER

View full text Add to dashboard Cite

Abstract-In this paper an improved particle swarm optimization algorithm (IPSO) for electromagnetic applications is proposed. In order to overcome the drawbacks of standard PSO, some improved mechanisms for velocity updating, the exceeding boundary control, global best perturbation and the simplified quadratic interpolation (SQI) operator are adopted. To show the effectiveness of the proposed algorithm, a selected set of numerical examples, concerned with linear as well as planar array, is presented. Simulation results show that the refined pinpointing search ability and the global search ability of the proposed algorithm are significantly improved when compared to the particle swarm optimization (PSO) and Genetic Algorithm (GA).

show abstract

Ultrawideband Optimized Profile Monopole Antenna by Means of Simulated Annealing Algorithm and the Finite Element Method

Cited by 39 publications

References 16 publications

Reliable Fast Frequency Sweep for Microwave Devices via the Reduced-Basis Method

Reliable Fast Frequency Sweep for Microwave Devices via the Reduced-Basis Method

Performance enhancement of multiband antennas through a two-stage optimization technique

An Improved Particle Swarm Optimization Algorithm for Pattern Synthesis of Phased Arrays

Contact Info

Product

Resources

About