Cognitive radio (CR) is one of the compelling ideas to solve the spectrum scarcity problem for rapid developments in wireless communication systems. In CR systems, signal detection for orthogonal frequency division multiplexing (OFDM) systems in severe noise environments is a key challenge. The area of practical primary user detection has not been explored in depth. The proposed method is an effective method for sensing OFDM applications, which are the practical primary users, for low signal-to-noise (SNR) cases. In the proposed method, the parallel combination of the comb filter and the time-domain autocorrelation function is exploited. The detection performance is measured for various OFDM system applications, including the IEEE 802.11a wireless LAN (WLAN) radio interface, long-term evaluation (LTE), and digital audio broadcasting (DAB) for various CP ratios under 16-quadrature amplitude modulation (16-QAM) and 64-quadrature amplitude modulation (64-QAM) over multipath Rayleigh fading channels with additive white Gaussian noise (AWGN). Furthermore, the OFDM sensing is possible in the presence of noise uncertainty and the sensing performance is compared under consideration with and without noise uncertainty cases. The simulation results demonstrated that our proposed method undoubtedly improves the sensing performances (up to 11 dB SNR gain) of practical primary users more than the conventional spectrum detection methods for low SNR cases.
Published in | American Journal of Networks and Communications (Volume 13, Issue 2) |
DOI | 10.11648/j.ajnc.20241302.12 |
Page(s) | 97-107 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
WLAN, LTE, DAB, Noise Uncertainty, SNR, Cognitive Radio
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APA Style
Haque, M., Sugiura, Y., Shimamura, T. (2024). Detection of Practical Primary Users in Severe Noise Environments for Cognitive Radio. American Journal of Networks and Communications, 13(2), 97-107. https://doi.org/10.11648/j.ajnc.20241302.12
ACS Style
Haque, M.; Sugiura, Y.; Shimamura, T. Detection of Practical Primary Users in Severe Noise Environments for Cognitive Radio. Am. J. Netw. Commun. 2024, 13(2), 97-107. doi: 10.11648/j.ajnc.20241302.12
@article{10.11648/j.ajnc.20241302.12, author = {Mousumi Haque and Yosuke Sugiura and Tetsuya Shimamura}, title = {Detection of Practical Primary Users in Severe Noise Environments for Cognitive Radio}, journal = {American Journal of Networks and Communications}, volume = {13}, number = {2}, pages = {97-107}, doi = {10.11648/j.ajnc.20241302.12}, url = {https://doi.org/10.11648/j.ajnc.20241302.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20241302.12}, abstract = {Cognitive radio (CR) is one of the compelling ideas to solve the spectrum scarcity problem for rapid developments in wireless communication systems. In CR systems, signal detection for orthogonal frequency division multiplexing (OFDM) systems in severe noise environments is a key challenge. The area of practical primary user detection has not been explored in depth. The proposed method is an effective method for sensing OFDM applications, which are the practical primary users, for low signal-to-noise (SNR) cases. In the proposed method, the parallel combination of the comb filter and the time-domain autocorrelation function is exploited. The detection performance is measured for various OFDM system applications, including the IEEE 802.11a wireless LAN (WLAN) radio interface, long-term evaluation (LTE), and digital audio broadcasting (DAB) for various CP ratios under 16-quadrature amplitude modulation (16-QAM) and 64-quadrature amplitude modulation (64-QAM) over multipath Rayleigh fading channels with additive white Gaussian noise (AWGN). Furthermore, the OFDM sensing is possible in the presence of noise uncertainty and the sensing performance is compared under consideration with and without noise uncertainty cases. The simulation results demonstrated that our proposed method undoubtedly improves the sensing performances (up to 11 dB SNR gain) of practical primary users more than the conventional spectrum detection methods for low SNR cases.}, year = {2024} }
TY - JOUR T1 - Detection of Practical Primary Users in Severe Noise Environments for Cognitive Radio AU - Mousumi Haque AU - Yosuke Sugiura AU - Tetsuya Shimamura Y1 - 2024/10/31 PY - 2024 N1 - https://doi.org/10.11648/j.ajnc.20241302.12 DO - 10.11648/j.ajnc.20241302.12 T2 - American Journal of Networks and Communications JF - American Journal of Networks and Communications JO - American Journal of Networks and Communications SP - 97 EP - 107 PB - Science Publishing Group SN - 2326-8964 UR - https://doi.org/10.11648/j.ajnc.20241302.12 AB - Cognitive radio (CR) is one of the compelling ideas to solve the spectrum scarcity problem for rapid developments in wireless communication systems. In CR systems, signal detection for orthogonal frequency division multiplexing (OFDM) systems in severe noise environments is a key challenge. The area of practical primary user detection has not been explored in depth. The proposed method is an effective method for sensing OFDM applications, which are the practical primary users, for low signal-to-noise (SNR) cases. In the proposed method, the parallel combination of the comb filter and the time-domain autocorrelation function is exploited. The detection performance is measured for various OFDM system applications, including the IEEE 802.11a wireless LAN (WLAN) radio interface, long-term evaluation (LTE), and digital audio broadcasting (DAB) for various CP ratios under 16-quadrature amplitude modulation (16-QAM) and 64-quadrature amplitude modulation (64-QAM) over multipath Rayleigh fading channels with additive white Gaussian noise (AWGN). Furthermore, the OFDM sensing is possible in the presence of noise uncertainty and the sensing performance is compared under consideration with and without noise uncertainty cases. The simulation results demonstrated that our proposed method undoubtedly improves the sensing performances (up to 11 dB SNR gain) of practical primary users more than the conventional spectrum detection methods for low SNR cases. VL - 13 IS - 2 ER -