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An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks

Champa Tanga1 , Tage Kunya2

Section:Research Paper, Product Type: Journal Paper
Volume-12 , Issue-10 , Page no. 8-14, Oct-2024

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v12i10.814

Online published on Oct 31, 2024

Copyright © Champa Tanga, Tage Kunya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Champa Tanga, Tage Kunya, “An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks,” International Journal of Computer Sciences and Engineering, Vol.12, Issue.10, pp.8-14, 2024.

MLA Style Citation: Champa Tanga, Tage Kunya "An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks." International Journal of Computer Sciences and Engineering 12.10 (2024): 8-14.

APA Style Citation: Champa Tanga, Tage Kunya, (2024). An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks. International Journal of Computer Sciences and Engineering, 12(10), 8-14.

BibTex Style Citation:
@article{Tanga_2024,
author = {Champa Tanga, Tage Kunya},
title = {An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2024},
volume = {12},
Issue = {10},
month = {10},
year = {2024},
issn = {2347-2693},
pages = {8-14},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5721},
doi = {https://doi.org/10.26438/ijcse/v12i10.814}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v12i10.814}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5721
TI - An Investigation into Threshold Selection Methodologies for Spectrum Sensing Techniques in Cooperative Cognitive Radio Networks
T2 - International Journal of Computer Sciences and Engineering
AU - Champa Tanga, Tage Kunya
PY - 2024
DA - 2024/10/31
PB - IJCSE, Indore, INDIA
SP - 8-14
IS - 10
VL - 12
SN - 2347-2693
ER -

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Abstract

This study investigate the optimal conditions for variable SNR values and appropriate threshold values can be examined through concurrent analysis of Pf and Pm when employing energy detector techniques for spectrum sensing. As the proposed method demonstrates higher Pm and lower Pm at low SNR, it fulfills the EDSS optimality criteria for low SNR environments. Additionally, this approach enables threshold verification at high SNR values, and subsequent research could focus on primary user detection. Furthermore, diverse sensing techniques can be applied to contemporary wireless technologies. Additional investigation of various parameters utilizing different methodologies is strongly recommended to improve spectrum sensing outcomes in cognitive radio networks.

Key-Words / Index Term

Spectrum Sensing, Cooperative Cognitive Radio Network, SNR

References

[1] G. Verma and O. P. Sahu, "Intelligent selection of threshold in cognitive radio system," Telecommunication Systems, vol. 63, no. 4, pp. 547-556, 2016.
[2] C. Charan and R. Pandey, "Intelligent selection of threshold in covariance-based spectrum sensing for cognitive radio networks," Wireless Networks, vol. 24, no. 8, pp. 3267-3279, 2018.
[3] K. Umebayashi, K. Hayashi, and J. J. Lehtomäki, "Threshold-setting for spectrum sensing based on statistical information," IEEE Communications Letters, vol. 21, no. 7, pp. 1585-1588, 2017.
[4] G. Verma and O. P. Sahu, "Intelligent selection of threshold in cognitive radio system," Telecommunication Systems, vol. 63, no. 4, pp. 547-556, 2016.
[5] S. Koley, V. Mirza, S. Islam, and D. Mitra, "Gradient based real-time spectrum sensing at low SNR," IEEE Communications Letters, vol. 19, no. 3, pp. 391-394, 2015.
[6] V. Sharma and S. Joshi, "A literature review on spectrum sensing in cognitive radio applications," in Proceedings of the Second International Conference on Intelligent Computing and Control Systems (ICICCS 2018), 2018.
[7]. K. Kockaya and I. Develi, "Spectrum sensing in cognitive radio networks: threshold optimization and analysis," EURASIP Journal on Wireless Communications and Networking, vol. 2020, Article number: 255, 2020.
[8] A. Kumar, P. Thakur, S. Pandit, and G. Singh, "Analysis of optimal threshold selection for spectrum sensing in a cognitive radio network: an energy detection approach," Wireless Networks, vol. 25, pp. 3917-3931, 2019.
[9]A. Kumar, P. Thakur, S. Pandit, and G. Singh, "Threshold selection analysis of spectrum sensing for cognitive radio network with censoring based imperfect reporting channels," Wireless Networks, vol. 27, no. 4, pp. 19, Jan. 2021
[10] O. H. Toma and M. López-Benítez, "Cooperative spectrum sensing: A new approach for minimum interference and maximum utilization," in 2021 IEEE International Conference on Communications, pp. 1-6, 2021.
[11] G. Yu, H. Wang, and W. Du, "Cooperative spectrum sensing algorithm to overcome noise fluctuations based on energy detection in sensing systems," Wireless Communications and Mobile Computing, vol. 2021, no. 9, pp. 1-8, Mar. 2021.
[12] H. Urkowitz, "Energy detection of unknown deterministic signals," in Proceedings of the IEEE, vol. 55, no. 4, pp. 523-531, April 1967
.[13] F. Salahdine, E. Ghribi, and N. Kaabouch, "A cooperative spectrum sensing scheme based on compressive sensing for cognitive radio networks," International Journal of Digital Information and Wireless Communications, vol. 9, no. 2, Nov. 2019
[14] A. Kumar, P. Thakur, S. Pandit, and G. Singh, "Fixed and dynamic threshold selection criteria in energy detection for cognitive radio communication systems," in Proceedings of the 10th IEEE International Conference on Contemporary Computing (IC3), India, pp. 1-6, 2017.
[15] Rishika Dubey, Vineeta Saxena Nigam, "High Spectrum Efficiency and Low BER of Massive MIMO System using Spectrum Sensing Cognitive Radio Network", International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.287-291, 2019.
[16] Aasia Rehman, "Detection Of Primary User Emulation Attack in Cognitive Radio Networks Based On TDOA using Grey Wolf Optimizer", International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.332-337, 2019.
[17] Praneeth P. Jain, Pradeep R. Pawar, Prajwal Patil, Devasis Pradhan, "Narrowband Spectrum Sensing in Cognitive Radio: Detection Methodologies", International Journal of Computer Sciences and Engineering, Vol.7, Issue.11, pp.105-113, 2019.