A Distributed Weighted Consensus Based Cooperative Spectrum Sensing Scheme using Cyclostationary Detection
Abstract
Detection of primary users (PUs) in the pres- ence of interference and noise and improvement of spec- trum utilization is one of the aims of cognitive radio (CR). In this paper, a fully distributed cooperative spectrum sens- ing scheme based on cyclostationary features techniques is proposed. The primary signal detection is realized by an OFDM fast spectrum sensing algorithm, then each secondary user (SU) choses the information exchanging rate according to the estimated average signal to noise ratio (SNR). The SUs exchange their own measurement with their local neighbors to make decision about the primary user. Simulation results show that the proposed consensus scheme can have significant lower mission detection and probability of false alarm. We also show that the proposed method performs better than the existing consensus energy detector based approach.
How to cite this article:
Barkat E, Wickert M, Laroussi T. A Distributed
Weighted Consensus Based Cooperative
Spectrum Sensing Scheme using Cyclostationary
Detection. J Adv Res Sig Proc Appl 2020; 3(1):
27-33
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[2] J. Mitola, “Cognitive radio for flexible mobile multimedia com- munications,” in Mobile Multimedia Communications, 1999.(Mo- MuC’99) 1999 IEEE International Workshop on. IEEE, 1999, pp. 3–10.
[3] F. R. Yu, H. Tang, M. Huang, P. Mason, and Z. Li, “Distributed cooperative spectrum sensing in mobile ad hoc networks with cognitive radios,” arXiv preprint arXiv:1104.5539, 2011.
[4] Q. Zhang, Y. Zhang, M. Song, and D. Dang, “Self-coexistence strategy in heterogeneous cognitive radio networks,” Interna- tional Journal of Communications, Network and System Sciences, vol. 10, no. 05, p. 311, 2017.
[5] A. Ghasemi and E. S. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environments,” in New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005. 2005 First IEEE International Symposium on. IEEE, 2005, pp. 131–136.
[6] E. C. Peh, Y.-C. Liang, Y. L. Guan, and Y. Zeng, “Cooperative spectrum sensing in cognitive radio networks with weighted decision fusion schemes,” IEEE Transactions on Wireless Com- munications, vol. 9, no. 12, pp. 3838–3847, 2010.
[7] F. S. Cattivelli and A. H. Sayed, “Distributed detection over adaptive networks using diffusion adaptation,” IEEE Transactions on Signal Processing, vol. 59, no. 5, pp. 1917–1932, 2011.
[8] W. Ejaz, N. ul Hasan, H. S. Kim, and M. A. Azam, “Fully distributed cooperative spectrum sensing for cognitive radio ad hoc networks,” in 2011 Frontiers of Information Technology. IEEE, 2011, pp. 9–13.
[9] H. Urkowitz, “Energy detection of unknown deterministic sig- nals,” Proceedings of the IEEE, vol. 55, no. 4, pp. 523–531, 1967.
[10] R. Tandra and A. Sahai, “Fundamental limits on detection in low snr under noise uncertainty,” in Wireless Networks, Communica- tions and Mobile Computing, 2005 International Conference on, vol. 1. IEEE, 2005, pp. 464–469.
[11] T. Yucek and H. Arslan, “A survey of spectrum sensing algo- rithms for cognitive radio applications,” IEEE communications surveys & tutorials, vol. 11, no. 1, pp. 116–130, 2009.
[12] K. Berbra, M. Barkat, F. Gini, M. Greco, and P. Stinco, “A fast spectrum sensing for cp-ofdm cognitive radio based on adaptive thresholding,” Signal Processing, vol. 128, pp. 252–261, 2016.
[13] Z. Li, F. R. Yu, and M. Huang, “A distributed consensus-based cooperative spectrum-sensing scheme in cognitive radios,” IEEE Transactions on Vehicular Technology, vol. 59, no. 1, pp. 383– 393, 2010.
[14] W. Zhang, Z. Wang, H. Liu, Y. Guo, Y. Chen, and J. Mitola III, “Distributed cooperative spectrum sensing using weighted av- erage consensus,” in Global Telecommunication Conference (GLOBECOM 2011), 2011.
[15] R. Tandra and A. Sahai, “Snr walls for feature detectors,” in New Frontiers in Dynamic Spectrum Access Networks, 2007. DySPAN 2007. 2nd IEEE International Symposium on. IEEE, 2007, pp. 559–570.
[16] S. Chaudhari, V. Koivunen, and H. V. Poor, “Autocorrelation- based decentralized sequential detection of ofdm signals in cog- nitive radios,” IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2690–2700, 2009.
[17] X. Zhai, H. Haigen, and Z. Guoxin, “Optimal threshold and weighted cooperative data combining rule in cognitive radio network,” in Communication Technology (ICCT), 2010 12th IEEE International Conference on. IEEE, 2010, pp. 1464–1467.
[18] C. Zhang, X. Wang, X. Guan, and H.-H. Chen, “Quality-of- service in cognitive radio networks with collaborative sensing,” in Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE. IEEE, 2009, pp. 1–5.
[19] M. K. Simon and M.-S. Alouini, Digital communication over fading channels. John Wiley & Sons, 2005, vol. 95.
[20] K. Berbra, M. Barkat, and A. Anou, “Pn code acquisition using smart antenna and adaptive thresholding cfar based on ordered data variability for cdma communications,” Progress In Electromagnetics Research, vol. 57, pp. 139–155, 2014.
[21] A. Sofwan, M. Barkat, and S. A. AlQahtani, “Pn code acquisi- tion using smart antennas and adaptive thresholding for spread spectrum communications,” Wireless Networks, vol. 22, no. 1, pp. 223–234, 2016.
[22] V. P. Ipatov, Spread spectrum and CDMA: principles and appli- cations. John Wiley & Sons, 2005.
[23] R. Schafer, “Discrete-time signal processing,” 1989.
[24] M. Barkat and P. K. Varshney, “Decentralized cfar signal detec- tion,” IEEE Transactions on Aerospace and Electronic Systems, vol. 25, no. 2, pp. 141–149, 1989.
[25] T. E. Bogale and L. Vandendorpe, “Multi-cycle cyclostationary based spectrum sensing algorithm for ofdm signals with noise uncertainty in cognitive radio networks,” in Military Communi- cations Conference, 2012-MILCOM 2012. IEEE, 2012, pp. 1–6.
[26] A. Goldsmith, Wireless communications. Cambridge university press, 2005.
[27] H. Sadeghi, P. Azmi, and H. Arezumand, “Cyclostationarity- based soft cooperative spectrum sensing for cognitive radio networks,” IET communications, vol. 6, no. 1, pp. 29–38, 2012.
[28] F. Visser, G. J. Janssen, and P. Pawelczak, “Multinode spectrum sensing based on energy detection for dynamic spectrum access,” in Vehicular Technology Conference, 2008. VTC Spring 2008. IEEE. IEEE, 2008, pp. 1394–1398.
Published
2021-10-03
How to Cite
BARKAT, Enfel.
A Distributed Weighted Consensus Based Cooperative Spectrum Sensing Scheme using Cyclostationary Detection.
Journal of Advanced Research in Signal Processing and Applications, [S.l.], v. 2, n. 1, p. 27-33, oct. 2021.
Available at: <http://www.thejournalshouse.com/index.php/SignalProcessing-Applications/article/view/453>. Date accessed: 01 may 2024.
Section
Review Article
