On the performance of various 5G signals sensing based on hybrid filter

The 5G wireless communication system is promised to exploit many kinds of waveform for satisfying various requirements to transmit huge size of data. The Cognitive Radio Networks based 5G can coexist among various kinds of signal to enrich every 5G wireless system with necessary frequency bands rega...

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Main Authors: Algriree, Waleed, Sulaiman, Nasri, M. Isa, Maryam, Sahbudin, Ratna K. Z., Hassan, Siti L. M., Salman, Emad Hmood
Format: Article
Published: Springer 2022
Online Access:http://psasir.upm.edu.my/id/eprint/102391/
https://link.springer.com/article/10.1007/s10776-022-00589-0
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.1023912023-05-18T03:14:18Z http://psasir.upm.edu.my/id/eprint/102391/ On the performance of various 5G signals sensing based on hybrid filter Algriree, Waleed Sulaiman, Nasri M. Isa, Maryam Sahbudin, Ratna K. Z. Hassan, Siti L. M. Salman, Emad Hmood The 5G wireless communication system is promised to exploit many kinds of waveform for satisfying various requirements to transmit huge size of data. The Cognitive Radio Networks based 5G can coexist among various kinds of signal to enrich every 5G wireless system with necessary frequency bands regardless the kind of waveform. However, most of Spectrum Sensing (SS) techniques are proposed to detect only one kind of waveform that is used in the 5G wireless communication system. To address this issue, designing a SS technique to sense various kinds of waveforms for the 5G wireless communication system is necessary to help this system. In this paper, a SS technique have been proposed for accurately sensing different waveform kinds (F-OFDM, UFMC, and FBMC) through a 5G network where these waveforms have different rates of some data like cyclic prefix, signal length, energy, mapper, and shape. The proposed sensing technique includes three stages; cosine filtering, Bartlett segmenting, and hamming windowing. The cosine filtering function is differentiating between the traffic signals based 5G and noise. Then, the filtered signals are segmented with the help of the Bartlett Segmenting for decreasing the rest noise then every segment is windowed using the Hamming windowing for maintaining the signal resolution. The simulation results revealed a significant detection performance regarding to the following numerical results; detection probability is ≥ 0.95 and false alarm probability is < 0.05, for less than zero dB of signal-to-noise ratio and a lower complexity level. Furthermore, the detection performance of the proposed SS technique is better than that of the related works as shown in a comparison table and a graphical manner. Springer 2022-12-12 Article PeerReviewed Algriree, Waleed and Sulaiman, Nasri and M. Isa, Maryam and Sahbudin, Ratna K. Z. and Hassan, Siti L. M. and Salman, Emad Hmood (2022) On the performance of various 5G signals sensing based on hybrid filter. International Journal of Wireless Information Networks, 30. pp. 42-57. ISSN 1068-9605; ESSN: 1572-8129 https://link.springer.com/article/10.1007/s10776-022-00589-0 10.1007/s10776-022-00589-0
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The 5G wireless communication system is promised to exploit many kinds of waveform for satisfying various requirements to transmit huge size of data. The Cognitive Radio Networks based 5G can coexist among various kinds of signal to enrich every 5G wireless system with necessary frequency bands regardless the kind of waveform. However, most of Spectrum Sensing (SS) techniques are proposed to detect only one kind of waveform that is used in the 5G wireless communication system. To address this issue, designing a SS technique to sense various kinds of waveforms for the 5G wireless communication system is necessary to help this system. In this paper, a SS technique have been proposed for accurately sensing different waveform kinds (F-OFDM, UFMC, and FBMC) through a 5G network where these waveforms have different rates of some data like cyclic prefix, signal length, energy, mapper, and shape. The proposed sensing technique includes three stages; cosine filtering, Bartlett segmenting, and hamming windowing. The cosine filtering function is differentiating between the traffic signals based 5G and noise. Then, the filtered signals are segmented with the help of the Bartlett Segmenting for decreasing the rest noise then every segment is windowed using the Hamming windowing for maintaining the signal resolution. The simulation results revealed a significant detection performance regarding to the following numerical results; detection probability is ≥ 0.95 and false alarm probability is < 0.05, for less than zero dB of signal-to-noise ratio and a lower complexity level. Furthermore, the detection performance of the proposed SS technique is better than that of the related works as shown in a comparison table and a graphical manner.
format Article
author Algriree, Waleed
Sulaiman, Nasri
M. Isa, Maryam
Sahbudin, Ratna K. Z.
Hassan, Siti L. M.
Salman, Emad Hmood
spellingShingle Algriree, Waleed
Sulaiman, Nasri
M. Isa, Maryam
Sahbudin, Ratna K. Z.
Hassan, Siti L. M.
Salman, Emad Hmood
On the performance of various 5G signals sensing based on hybrid filter
author_facet Algriree, Waleed
Sulaiman, Nasri
M. Isa, Maryam
Sahbudin, Ratna K. Z.
Hassan, Siti L. M.
Salman, Emad Hmood
author_sort Algriree, Waleed
title On the performance of various 5G signals sensing based on hybrid filter
title_short On the performance of various 5G signals sensing based on hybrid filter
title_full On the performance of various 5G signals sensing based on hybrid filter
title_fullStr On the performance of various 5G signals sensing based on hybrid filter
title_full_unstemmed On the performance of various 5G signals sensing based on hybrid filter
title_sort on the performance of various 5g signals sensing based on hybrid filter
publisher Springer
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/102391/
https://link.springer.com/article/10.1007/s10776-022-00589-0
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