TELKOMNIKA Telecommunication, Computing, Electronics and Control
Predicting the notch band frequency of an ultra-wideband antenna using artificial neural networks

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Predicting the notch band frequency of an ultra-wideband antenna using artificial neural networks

Artificial neural networks
K-fold cross validation
Ultra-wideband antenna

In this paper we propose to predict the notch frequency of an ultra-wideband
(UWB) antenna which operates in the frequency band from 3.85 GHz to 12.38
GHz. The prediction of the notch frequency in order to avoid interferences
between (WLAN) IEEE802.11a and HIPERLAN/2 WLAN applications and
UWB technology is achieved using the artificial neural networks (ANN)
technique. The developed ANN is optimized with the help of K-fold cross
validation method which allows us to divide the datasets into 10 subsets in the
training phase. The simulated datasets are generated by controlling high
frequency structural simulator (HFSS) from MATLAB using a VB script. The
performance of the ANN technique is assessed using some statistical criteria.
During the training process, the mean absolute percentage error (MAPE)
between the simulated and the predicted ANN notch frequencies is 0,125. A
comparison between simulated, theoretical, and ANN results has been
achieved during the test and validation process, good accuracy is obtained
between the simulated and the ANN predictions. The proposed UWB antenna
exhibits a notch band from 5.1 GHz to 6.0 GHz with a notch frequency of
approximately 5.51 GHz.

Lahcen Aguni, Samira Chabaa, Saida Ibnyaich, Abdelouhab Zeroual

http://journal.uad.ac.id/index.php/TELKOMNIKA

Aug 29, 2020

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