Volume 18, Issue 3 (September 2022)                   IJEEE 2022, 18(3): 147-154 | Back to browse issues page

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Fertas K, Fertas F, Tebache S, Mansoul A, Aksas R. Genetic Algorithm Based Approach for Frequency Switchable Dual-Band Patch Antenna. IJEEE 2022; 18 (3) :147-154
URL: http://ijeee.iust.ac.ir/article-1-2454-en.html
Genetic Algorithm Based Approach for Frequency Switchable Dual-Band Patch Antenna
K. Fertas , F. Fertas , S. Tebache , A. Mansoul , R. Aksas
Abstract:   (1476 Views)
In this paper, a frequency switchable antenna design using genetic algorithms (GAs) for dual band WiMAX (3.5GHz) and WLAN (5.2GHz) applications is proposed. The area of the radiating patch element is divided into 2 mm square cells, with each cell assigned a conducting or non-conducting characteristic. To realize frequency reconfiguration, switches are incorporated into appropriate locations to activate/deactivate corresponding cells. The on/off states of the switches are represented by the presence or absence of conductor, respectively. Hence, the proposed approach allows the antenna to operate as mono-band or dual-band radiator according to the desired application. Further, measurements and simulations are carried out and a reasonable agreement is achieved.
Keywords: Genetic Algorithm , Dual-Band Antenna , Switchable Frequency Band
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  • A frequency switchable antenna design using genetic algorithms (GAs) for dual band WiMAX (3.5GHz) and WLAN (5.2GHz) applications is proposed;
  • To realize frequency reconfiguration, switches are incorporated into appropriate locations to activate/deactivate corresponding cells;
  • The on/off states of the switches are represented by the presence or absence of conductor, respectively;
  • The proposed approach allows the antenna to operate as mono-band or dual-band radiator according to the desired application.

Type of Study: Research Paper | Subject: Antenna
Received: 2022/03/10 | Revised: 2024/05/13 | Accepted: 2022/06/29
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.