Phased arrays in communication system based on Taguchi-neural networks

Phased antenna array design is one of the most important electromagnetic optimization problems. This research combined the Taguchi method and artificial intelligence methods, used them as the prediction tool in designing parameters for the communication system, and then constructed a set of the optimal parameter analysis flow and steps. In this paper, we present an application of artificial neural networks in the electromagnetic domain. We particularly look at the multilayer perceptron network, which has been the most used of artificial neural networks architectures both in the electromagnetic domain and in the Taguchi optimization technique and describes the Taguchi method to optimize the excitations elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control. This paper investigates how the implementation of the signal processing in hardware affects the performance of the adaptive array antenna. The investigation is confined to uplink or receive antenna array only. Results of a prototype of antenna array with feeding values designed using the proposed techniques are also presented. Copyright © 2013 John Wiley & Sons, Ltd.