2008
DOI: 10.1163/156939308784160613
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Optimizing a PIFA Using a Genetic Algorithms Approach

Abstract: An optimized planar inverted F antenna (PIFA), used in mobile communications, is proposed in this paper. With the aid of the Genetic Algorithms (GA) optimization technique, a PIFA with a wide impedance bandwidth and a sufficient gain for use in mobile communications is presented. A comparison with results emerging from an application of the Finite Difference Time Domain (FDTD) method is demonstrated.

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Cited by 9 publications
(11 citation statements)
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“…Nevertheless, the bandwidth of each band depends on the complete hybrid device and it is not connected with only one parameter of the prototype. For this reason, the optimization process must take into account the variation of several parameters simultaneously [13][14][15].…”
Section: Numerical Simulation Results and Comparisonmentioning
confidence: 99%
See 1 more Smart Citation
“…Nevertheless, the bandwidth of each band depends on the complete hybrid device and it is not connected with only one parameter of the prototype. For this reason, the optimization process must take into account the variation of several parameters simultaneously [13][14][15].…”
Section: Numerical Simulation Results and Comparisonmentioning
confidence: 99%
“…Usually, the main problem of the optimization of antennas is that these devices must be simulated for each set of parameters, so the computation is usually time-consuming, and very few objective function evaluations are available to complete the optimization process in a reasonable time. In these conditions, soft-computing approaches work quite well, and specifically, there are several works in the literature applying novel meta-heuristics approaches, such as evolutionary computation algorithms to antennas optimization [13][14][15]. The good performance of these previous approaches even with the constrain of very few function evaluations, made us to consider a class of evolutionary computation algorithm to carry out the parameters' optimization of the hybrid PIFA-patch antenna.…”
Section: Introductionmentioning
confidence: 99%
“…The EM-like algorithm based optimization scheme is easy to implement. Therefore, it is suitable not only for problems of antenna arrays, but also for many other nonlinear optimization problems in electromagnetic waves [10][11][12][13][14][15][16][17][18][19][20].…”
Section: Discussionmentioning
confidence: 99%
“…The complex signals of 16 beams are transferred to beamforming computer, where the phase and amplitude adjustment are put into practice. Since the beam coverage is fixed, the phase and amplitude excitation coefficients were calculated previously by Genetic Algorithm according to the predefined radiation patterns [11][12][13][14]. Hartley image-rejection structure is designed to eliminate the overlapping image frequency caused by DFT filter bank analyzer.…”
Section: Signal Processing Of Digtial Bfnmentioning
confidence: 99%
“…It can be conclude that the k-th beam will be aliased with the |k − 2| beam, as the center frequency of filter is at 12.5 MHz (k = 1). If we adopt the low-pass filter, the aliasing frequency can't be cancelled, because of the asymmetry property of each beam's spectrum [14,15].…”
Section: Hartley Image Rejection Structurementioning
confidence: 99%