Artificial neural network approach for analyzing mutual coupling in a rectangular MIMO antenna

Abstract

A wideband rectangular patch antenna resonating at 3.5 GHz and 8 GHz frequencies is developed on a flexible substrate, which can be used for wearable applications. The proposed antenna gives a wide impedance bandwidth of 116%, operating from 2.5 GHz to 9.5 GHz, covering most of the ultra-wideband (UWB) operating frequency range. A two-element multiple-input multiple-output (MIMO) system is developed using the proposed antenna, and the mutual coupling between the two antennas for various separations and frequencies is analyzed by using artificial neural networks (ANNs). The neural structure is trained by using different ANN algorithms and a comparative study is made between them. It is shown that, quasi-Newton (QN) and quasi-Newton multi layer perceptron (QN-MLP) algorithms are better in terms of training, testing errors, and correlation coefficient.

Keywords

flexible substrate / multiple-input multiple-output (MIMO) systems / artificial neural networks (ANNs) / mutual coupling / impedance bandwidth

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg