A Modified Chicken Swarm Optimization Algorithm for Synthesizing Linear, Circular and Random Antenna Arrays

2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall) Pub Date : 2019-09-01 DOI:10.1109/VTCFall.2019.8891515

Geng Sun, Xiaohui Zhao, Shuang Liang, Yanheng Liu, Xu Zhou, Ying Zhang

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引用次数: 6

Abstract

Antenna arrays can enhance the directivity and save the transmission power of a communication system. Beam pattern optimization for reducing the maximum sidelobe level (SLL) is a classical electromagnetic problem in antenna arrays. In this paper, a novel improved chicken swarm optimization (ICSO) algorithm is proposed to suppress the maximum SLL of the linear antenna array (LAA), the circular antenna array (CAA) and the random antenna array (RAA). Three improved factors that are the global search, the weighting and the local search factors are introduced into the update method of the roosters, the hens and the chicks of the conventional chicken swarm optimization (CSO), respectively, to achieve better optimization results. Simulations are conducted to verify the performance of the proposed ICSO for suppressing the maximum SLL, and the results show that the proposed ICSO can obtain lower maximum SLL in LAA, CAA and RAA cases compared with several benchmark algorithms. Moreover, the stability of ICSO is evaluated and the results show that it outperforms the other algorithms.

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线性、圆形和随机天线阵列的改进鸡群优化算法

天线阵列可以增强通信系统的指向性，节省通信系统的传输功率。降低最大旁瓣电平的波束方向优化是天线阵列中的经典电磁问题。针对线性天线阵列(LAA)、圆形天线阵列(CAA)和随机天线阵列(RAA)的最大信噪比问题，提出了一种改进的鸡群优化算法(ICSO)。在常规鸡群优化(CSO)的公鸡、母鸡和雏鸡的更新方法中分别引入了全局搜索、加权和局部搜索三种改进因子，以获得更好的优化效果。仿真结果表明，与几种基准算法相比，所提ICSO在LAA、CAA和RAA情况下均能获得较低的最大SLL。此外，对ICSO算法的稳定性进行了评价，结果表明该算法优于其他算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)

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