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DOI: 10.14569/IJACSA.2020.0110297
PDF

Opportunistic use of Spectral Holes in Karachi using Convolutional Neural Networks

Author 1: Aamir Zeb Shaikh
Author 2: Shabbar Naqvi
Author 3: Minaal Ali
Author 4: Yamna Iqbal

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 2, 2020.

  • Abstract and Keywords
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Abstract: Wireless services appearing in the next generation wireless standard i.e. 6G include Internet of Everything (IoE), Holographic communications, smart transportation and smart cities require exponential rise in the bandwidth in addition to other requirements. The current static spectrum allocation policy does not allow any new entrant to exploit already grid-locked Radio Frequency (RF) spectrum. Hence, quest for larger bandwidth can be fulfilled through other technologies. These include exploiting sub-Terahertz band, Visible Light Communication and Cognitive Radio scheme or exploiting of RF bands in opportunistic fashion. Cognitive Radio is one of those engines to exploit the RF spectrum in secondary style. Cognitive Radio can use artificial intelligence driven algorithms to complete the task. Several intelligent algorithms can be used for better forecasting of spectral holes. Convolutional Neural Network (CNN) is a Deep Learning algorithm that can be used to predict the presence of a spectral holes that can be opportunistically exploited for efficient utilization of RF spectrum in secondary fashion. This paper investigates the performance of CNN for metropolitan Karachi city of Pakistan so that the users can be provided with uninterrupted access to the network even under busy hours. Dataset for the proposed setup is collected for 1805 MHz frequency band through NI 2901 Universal Software Radio Peripheral (USRP) devices. The root mean square error (RMSE) for the predicted results using CNN appears to be 81.02 at epoch of 200 and mini-batch loss of 3281.8. Based on the predicted results, it was concluded that CNN can be useful for investigating the possible opportunistic usage of RF spectrum, however, further investigation is required with different datasets.

Keywords: Cognitive Radio; Spectral hole; Deep Learning; Convolutional neural network (CNN)

Aamir Zeb Shaikh, Shabbar Naqvi, Minaal Ali and Yamna Iqbal, “Opportunistic use of Spectral Holes in Karachi using Convolutional Neural Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 11(2), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110297

@article{Shaikh2020,
title = {Opportunistic use of Spectral Holes in Karachi using Convolutional Neural Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110297},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110297},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {2},
author = {Aamir Zeb Shaikh and Shabbar Naqvi and Minaal Ali and Yamna Iqbal}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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