A parallel electromagnetic genetic-algorithm optimization (EGO) application for patch antenna design

被引：112

作者：

Villegas, FJ ^{[1
]}

Cwik, T

Rahmat-Samii, Y

Manteghi, M

机构：

[1] Aerosp Corp, El Segundo, CA 90245 USA

[2] Raytheon Elect Syst, El Segundo, CA 90245 USA

[3] CALTECH, Jet Prop Lab, High Performance Comp Grp, Pasadena, CA 91109 USA

[4] Univ Calif Los Angeles, Dept Elect Engn, Antenna Res & Measurement Lab, Los Angeles, CA 90095 USA

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2004年 / 52卷 / 09期

关键词：

genetic algorithms; method of moments (MoM); microstrip antenna; optimization; parallel computing;

D O I：

10.1109/TAP.2004.834071

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we describe an electromagnetic genetic algorithm (GA) optimization (EGO) application developed for the cluster supercomputing platform. A representative patch antenna design example for commercial wireless applications is detailed, which illustrates the versatility and applicability of the method. We show that EGO allows us to combine the accuracy of full-wave EM analysis with the robustness of GA optimization and the speed of a parallel computing algorithm. A representative patch antenna design case study is presented. We illustrate the use of EGO to design a dual-band antenna element for wireless communication (1.9 and 2.4 GHz) applications. The resulting antenna exhibits acceptable dual-band operation (i.e., better than - 10 dB return loss with 5.3 and 7% operating bandwidths at 1.9 and 2.4 GHz) while maintaining a cross-pol maximum field level at least 11 dB below the co-pol maximum.

引用

页码：2424 / 2435

页数：12

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