Application of Genetic Algorithm to optimize an Antenna Array

碩士 === 淡江大學 === 電機工程學系 === 88 === The wireless communication technique is developed well in this recently years , the idea of personal communications services (PCS) comes true. At the same time, the requirements of high communication quality are strictly. In order to achieve high quality...

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Bibliographic Details
Main Authors: Yu-Te Chung, 鍾源德
Other Authors: Ching-Lieh Li
Format: Others
Language:zh-TW
Published: 2000
Online Access:http://ndltd.ncl.edu.tw/handle/99503380678023400955
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Summary:碩士 === 淡江大學 === 電機工程學系 === 88 === The wireless communication technique is developed well in this recently years , the idea of personal communications services (PCS) comes true. At the same time, the requirements of high communication quality are strictly. In order to achieve high quality and data-rate, the overcome technique of multi-path and cochannel interference must be included. The well-known focuses are signal procession and antenna, so we also apply our tool to antenna array design. Genetic Algorithm is a very important and effective optimizer because of its global searching capability. In this decade, Genetic Algorithms are applied in various problems in many disciplines. In general, the searching result does not depend on the initial guess. In this thesis, the non-uniform probability density functions are employed in the crossover and mutation operators of GA during the course of searching to improve the computational efficiencies. The capability of escaping from local optima is improved such that the global optimum can be easily achieved. In addition, the convergence speed is also raised. Consider the fact that the parameters are encoded during the course of optimization using GA. After encoding, the most left hand side bit is the most significant bit MSB, while, the most right hand side bit is the least significant bit LSB. It is recognized that the correctness of those bits about the MSB determines thecorrectness of the parameters. The correctness of those bits about the LSB only determines the precision of the parameters. On the other hand, the changes of those bits near MSB imply a large range searching in parameter space, while, the changes of those bits near LSB imply a small range searching in parameter space. A linear antenna array consisting of isotropic elements is considered. The purpose is to find the array pattern that minimizes the side-lobe level from a given radiation pattern. Making an adjustment in excitation voltage’s amplitude and phase which allows one to find a set of array coefficients that yield a pattern meeting a specified side-lobe level. Furthermore, In real antenna array operation, excitation voltage error result in side-lobe level change is considered.