Pareto Optimal Design of Dual-Band Base Station Antenna Arrays Using Multi-Objective Particle Swarm Optimization With Fitness Sharing

被引：34

作者：

Goudos, Sotirios K. ^{[1
]}

Zaharis, Zaharias D. ^{[1
,2
]}

Kampitaki, Dimitra G. ^{[2
]}

Rekanos, Ioannis T. ^{[3
]}

Hilas, Costas S. ^{[4
]}

机构：

[1] Aristotle Univ Thessaloniki, Telecommun Ctr, Thessaloniki 54124, Greece

[2] Alexander Technol Educ Inst Thessaloniki, Dept Elect, Thessaloniki 57400, Greece

[3] Aristotle Univ Thessaloniki, Sch Engn, Div Phys, Thessaloniki 54124, Greece

[4] Inst Educ Technol, Dept Informat & Commun, Serres 62124, Greece

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2009年 / 45卷 / 03期

关键词：

Dual-band antenna array design; multi-objective optimization; Pareto optimization; particle swarm optimization; GENETIC ALGORITHM;

D O I：

10.1109/TMAG.2009.2012695

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：

The design of dual-band base station antennas under constraints for mobile communications is addressed in this paper. Given the antenna geometry, the method of moments (MoM) is used to compute the antenna characteristics. Two distinct multi-objective evolutionary algorithms are applied in order to find the Pareto front of the feasible solutions that satisfy the design constraints. In the present work, the Multi-Objective Particle Swarm Optimization with fitness sharing (MOPSO-fs) is compared with the Nondominated Sorting Genetic Algorithm-II (NSGA-II) in order to optimize the antenna geometry. Two design cases are presented. The first case is a five-element array operating in GSM1800/UMTS frequency bands. The second base station antenna array consists of six elements operating in UMTS/WLAN (2.4 GHz) frequency bands.

引用

页码：1522 / 1525

页数：4

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