Non-Cooperative Blind Spectrum Sensing for Primary Users in Cognitive Radio Networks with DS-CDMA
Subject Areas : Majlesi Journal of Telecommunication DevicesTahereh Bahraini 1 , Mohsen Eslami 2
1 - Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
2 - Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
Keywords: en,
Abstract :
Real-time spectrum sensing with precise accuracy is the most important step to establish cognitive radio networks (CRNs). Detecting the presence of primary users (PUs) that use DS-CDMA (Direct sequence code division multiple access) technique is a challenge for the secondary users (SUs) in CRNs. DS-CDMA transmissions with very low signal to noise ratio (SNR) results in a signal hidden below the noise level, therefore, the existing classic detection methods are not effective enough to sense the signals. In this paper, a method is proposed to resolve this challenge. The proposed method based on fluctuation of correlation estimators searches on a specific frequency band and detects primary user's signals. Simulation results show that the sensing performance of the method is better than other conventional schemes for dealing with DS-CDMA users.
[1] E. Hossain, D. Niyato, and Z. Han, Dynamic Spectrum Access and Management in Cognitive Radio Networks, New York, Cambridge university press, 2009.
[2] Federal Communications Commission, “Notice of proposed rulemaking and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies,” ET Docket No. 03-108, Feb 2005.
[3] T. Yucek, and H. Arsalan, “A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,” IEEE Communication Tutorials, vol. 11, no. 1, First Quarter 2009.
[4] A. De Domenico, E. C. Strinati, M. Di Benedetto, “A Survey on MAC Strategies for Cognitive Radio Networks,” Communications Surveys & Tutorials, IEEE, vol. 14, no. 1, pp.21-44, First Quarter 2012.
[5] Hongjian Sun; Nallanathan, A.; Cheng-Xiang Wang; Yunfei Chen, “Wideband spectrum sensing for cognitive radio networks: a survey,” IEEE Wireless Communications, vol. 20, no. 2, pp.74-81, April 2013.
[6] H.-S. Chen, W. Gao, and D. G. Daut, “Signature based spectrum sensing algorithms for IEEE 802.22 WRAN, ” in Proc IEEE Int. Conf. communications (ICC), Jun. 2007.
[7] A. Sonnenschein and P. M. Fishman, “Radiometric detectin of spread spectrum signals in noise of uncertainty power, ” IEEE Trans. Aerosp. Electron. Syst., vol. 28, no. 3, pp. 654-660. Jul. 1992.
[8] W. A. Gardner, “Exploitation of spectral redundancy in cyclostationary signals, ” IEEE Signal Process. Mag., vol. 8, no. 2, pp. 14-36, Apr. 1991.
[9] N. Han, S. H. Shon, J. O. Joo, and J. M. Kim, “Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems, ” in Proc. Int. Conf. Advanced Communication Technology, Korea, Fed. 2006.
[10] S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Englewood Cliffs, NJ: Prentice-Hall, vol. 2. 1998.
[11] Y. Zhang, B. Baggeroer, and J.G. Bellingham, “The total variance of a periodogram-based spectral estimate of a stochastic process with spectral uncertainty and its application to classifier design, ” IEEE Trans. Signal Process., vol. 53, no. 12, pp. 4556-4567, Dec. 2005.
[12] Yonghong Zeng, Ying-Chang Liang and Rui Zhang, "Blindly Combined Energy Detection for Spectrum Sensing in Cognitive Radio," IEEE, Signal Processing Letters, vol.15, no., pp.649-652, 2008.
[13] Zhipeng Deng, Lianfeng Shen, Nan Bao, Bailong Su, Jintao Lin and Dayang Wang, “Autocorrelation based detection of DSSS signal for cognitive radio system,” 2011 International Conference on Wireless Communications and Signal Processing (WCSP), Nov. 2011.
[14] G. Burel, “Detection of Spread Spectrum Transmissions Using Fluctuation of Correlation Estimators,” in Proc. IEEE-ISPACS, Honolulu, Hawai’i, USA, Nov. 5-8, 2000.
[15] Zayen, B., Hayar, A.M. and Nussbaum, D., “Blind Spectrum Sensing for Cognitive Radio Based on Model Selection,” in Proc. 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), May 2008.