期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：9
DOI：10.15680/IJIRCCE.2015. 0309146
出版社：S&S Publications
摘要：A Nonlinear Gradient Descent algorithm (NGD) is an iterative method that is given an initial point andfollows the negative of the gradient in order to move the point towards a critical point, which is hopefully the desiredlocal minimum. Nonlinear gradient descent is a popular algorithm for very large scale optimization problems, becauseit is easy to implement and can handle black box functions [1]. In Smart Antennas (SA) both Half Power Beam Width(HPBW) and Side Lobe Level (SLL) are low values to get good performance. However to design smart antennas withminimum side lobe level, and HPBW, Nonlinear gradient descent algorithm gives the good performance on HPBW andSLL. This NGD algorithm is used for adaptive array smart antennas, because these arrays allows the antenna to steersthe beam pattern in order to enhance the reception of a desired signal, while simultaneously suppressing interferingsignals through complex weight selection.
