The study of the ground plane effect on a Multiband PIFA Antenna by using Genetic Algorithm and Particle Swarm Optimization

Wakrim, Layla; Ibnyaich, Saida; Hassani, Moha M’Rabet

doi:10.1590/2179-10742016v15i4626

Cited by 18 publications

(7 citation statements)

References 24 publications

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“…6) Engineering Ground Plane: Impedance matching plays an important role in the efficient working of the antenna. If the ground plane structure is changed, the impedance matching and hence the size of the antenna changes [67]. One way to achieve that is making a slot in the ground plane to alter the path of return current.…”

Section: ) Use Of Higher Operating Frequencymentioning

confidence: 99%

Implantable Antennas for Bio-Medical Applications

Malik

Sant

Ajmal

et al. 2021

IEEE J. Electromagn. RF Microw. Med. Biol.

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Antenna design considerations for implantable devices in remote telehealth systems Take-Home Messages • Implantable sensors are pivotal to telehealth systems enabling continuous monitoring of a patient's vital health signs wirelessly. • Antennas are an integral element of these systems whose design is a complex task due to harsh and highly volatile in-body environment and requirements of robust and reliable performance while offering miniature structure, patient safety and biocompatibility. • A comprehensive critical review on the antenna design for implantable medical devices highlighting requirements, challenges, antenna types and human body effects on their performance shows that slotted patch antennas operating at higher frequencies can serve the purpose optimally. • The slotted patch antenna designed in the light of recommendations made offers a small size of 7.5×5×0.25 mm 3 with a-10 dB bandwidth of 25 MHz, a near-omnidirectional pattern and a gain of 1.7 dBi. • The paper can serve as a reference for the antenna designers working in the field of implantable devices providing state-of-the-art, current advancements, requirements, challenges as well as design rules.

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Section: ) Use Of Higher Operating Frequencymentioning

confidence: 99%

Implantable Antennas for Bio-Medical Applications

Malik

Sant

Ajmal

et al. 2021

IEEE J. Electromagn. RF Microw. Med. Biol.

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“…xx (6) The properties of the mean function and covariance function of GP are determined by a set of hyper parameters, and the maximum likelihood function can be used to find the optimal hyper parameters. By establishing the log likelihood function of the conditional probability of the training samples, the partial derivative of the hyper parameter is obtained, and then the conjugate gradient optimization method is used to find the optimal solution of the hyper parameter.…”

Section: B Gaussian Processmentioning

confidence: 99%

“…With the rapid development of computer field, computer aided design (CAD) technology has been greatly improved, and it is also used for simulation design of electromagnetic problems [1], generally using full-wave electromagnetic simulation software including high frequency structural simulator (HFSS), Computer Simulation Technology (CST), etc. When optimizing the electromagnetic problems, global optimization algorithms, such as particle swarm optimization (PSO) [2], [3], [4], [5], genetic algorithm (GA) [6], [7], [8] ant colony optimization (ACO) [9], [10], [11] etc., are usually used in combination with electromagnetic simulation software. However, this process repeatedly calls electromagnetic simulation software for electromagnetic performance evaluation, which is very time-consuming.…”

Section: Introductionmentioning

confidence: 99%

Antenna Modeling Based on Two-Stage Gaussian Process Considering Sensitivity Information

Tian

2021

IEEE Access

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For antenna modeling and optimization design, high-fidelity full-wave electromagnetic simulation software can generally be used to obtain training samples. However, this process takes a long time. To solve this problem, a two-stage Gaussian process (GP) considering electromagnetic sensitivity information is proposed. Based on the coarse grid and fine grid of electromagnetic simulation software, the first stage learns the mapping relationships of antenna performance and sensitivity of each parameter, simultaneously. In the second stage, the accurate surrogates are established based on the mapping relationships above obtained. Because the method in this study takes sensitivity information into consideration during the modeling process, it can better reflect the mapping relationship between antenna input and output, which can develop a more accurate surrogate model. The proposed two-stage GP surrogate model considering sensitivity information can significantly reduce the demand of high-fidelity training samples for modeling, and greatly save the simulation time of calling electromagnetic simulation software. Therefore, this method is more suitable for the problems of insufficient electromagnetic simulation samples. The proposed approach is evaluated by modeling and optimization of an inverted F antenna and an ultra-wideband planar monopole antenna. The results show that the method has high modeling accuracy with limited training samples given by high-fidelity electromagnetic simulation, which further verify its effectiveness and efficiency.

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“…Furthermore, the best position among all the particles obtained so far in the population is kept track of as → [19]. The particle's velocity update and position update are the main PSO operators, which can be expressed as [20][21][22]…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Multiband Operation and Performance Enhancement of the PIFA Antenna by Using Particle Swarm Optimization and Overlapping Method

Wakrim

Ibnyaich

Hassani

2017

Applied Computational Intelligence and Soft Computing

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Recently, the demand for wireless devices that support multiband frequency has increased. The integration of such technology in mobile communication system has led to a great demand in developing small size antenna with multiband operation, which is able to operate in the required system. In this paper, a novel type planar inverted F antenna (PIFA) with gridded ground plane structure and overlapping cells is presented. By controlling the overlapping size, we improve the characteristics of the proposed antenna. This antenna is developed to achieve multiband operation with small size and good performance. The particle swarm optimization (PSO) is employed to a PIFA antenna to get rid of the limitations of single band operation by searching the optimal localization and length of linear slots on the ground plane to give triband operation. This PIFA antenna can be integrated to operate for several mobile applications as Bluetooth/WLAN, WIMAX, and 4G (UMTS2100, LTE). The optimized antenna is simulated by both Ansoft HFSS and computer simulation technology microwave studio (CSTMWS) in terms of S-parameters. A good agreement between simulated performances by both software types is achieved. A parametric study is made to analyze the effect of different PIFA parameters on the operating frequency and the reflection coefficient in order to enhance the antenna performances. In these frequency bands, the antenna has nearly omnidirectional radiation pattern.

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The study of the ground plane effect on a Multiband PIFA Antenna by using Genetic Algorithm and Particle Swarm Optimization

Cited by 18 publications

References 24 publications

Implantable Antennas for Bio-Medical Applications

Implantable Antennas for Bio-Medical Applications

Antenna Modeling Based on Two-Stage Gaussian Process Considering Sensitivity Information

Multiband Operation and Performance Enhancement of the PIFA Antenna by Using Particle Swarm Optimization and Overlapping Method

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