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2016-04-07
Pattern Synthesis Using Hybrid Fourier-Neural Networks for IEEE 802.11 MIMO Application
By
Elies Ghayoula,

    Dr. Elies Ghayoula

    National Engineering School of Tunis

    ENIT, Tunisia Tunis EL Manar University

    Tunisia

    Homepage

Ridha Ghayoula,

    Dr. Ridha Ghayoula

    Faculté des Sciences de Tunis

    Campus Universitaire Tunis EL-manar

    Tunisia

    Homepage

Mohamed Haj-Taieb,

    Dr. Mohamed Haj-Taieb

    Department of Electrical and Computer Engineering

    Laval University

    Canada

    Homepage

Jean-Yves Chouinard,

    Dr. Jean-Yves Chouinard

    Department of Electrical and Computer Engineering

    Laval University

    Canada

    Homepage

Ammar Bouallegue

    Dr. Ammar Bouallegue

    National Engineering School of Tunis

    ENIT, Tunisia Tunis EL Manar University

    Tunisia

    Homepage

Progress In Electromagnetics Research B, Vol. 67, 45-58, 2016
doi:10.2528/PIERB16021601 | Google Scholar

Abstract
In this paper, the application of Artificial Neural Network (ANN) with back-propagation algorithm and weighted Fourier method are used for the synthesis of antenna arrays. The neural networks facilitate the modelling of antenna arrays by estimating the phases. The most important synthesis problem is to find the weights of the linear antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the side lobe level. This technique is used to prove its effectiveness in improving the performance of the antenna array. To achieve this goal, antenna array for Wi-Fi IEEE 802.11a with frequency at 2.4 GHz to 2.5 GHz is implemented using Hybrid Fourier-Neural Networks method. To verify the validity of the technique, several illustrative examples of uniform excited array patterns with the main beam are placed in the direction of the useful signal. The neural network synthesis method not only allows to establish important analytical equations for the synthesis of antenna array, but also provides a great flexibility between the system parameters in input and output which makes the synthesis possible due to the explicit relation given by them.
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Citation
Elies Ghayoula, Ridha Ghayoula, Mohamed Haj-Taieb, Jean-Yves Chouinard, and Ammar Bouallegue, "Pattern Synthesis Using Hybrid Fourier-Neural Networks for IEEE 802.11 MIMO Application," Progress In Electromagnetics Research B, Vol. 67, 45-58, 2016.
doi:10.2528/PIERB16021601
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