Abstract
In cognitive radio (CR), a transmitter/receiver can detect intelligently the communication channels that are in use and those that are not, and can move in the unused channels. This can be achieved by the means of spectrum sensing (SS) operation. The concept in spectrum sensing aims to maximize the use of available radio frequencies of the spectrum while minimizing interference with other users. Different techniques are presented in the literature. In this paper, we proposed a spectrum sensing approach based on the energy detector (ED) method combined with random sampling. This approach is performed in cognitive radio systems to analyze the occupancy of radio frequency spectrum. The performance of the proposed approach is evaluated in terms of the false alarm probability and compared to the uniform sampling case in order to show the utility of the use of random sampling. To complete our theoretical and simulation study, we are interested in the implementation of our solution using a real FM radio signal. The analyzed signal is an FM radio signal captured under GNU-radio environment. The performance of this application is evaluated in terms of the receiver operating characteristic curves (ROC curves) and in terms of the false alarm probability for different values of signal to noise ratio (SNR) in order to demonstrate the feasibility of spectrum sensing operation with a random sampling mode. The obtained results show that random sampling makes it possible to overcome forbidden band restriction encountered with uniform sampling mode.
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References
J. Palicot, De la radio logicielle à la radio intelligente (Institut Télécom et Lavoisier, Paris, 2010)
J. Mitola, G.Q. Maguire, Cognitive radio: making software radios more personal. IEEE Pers. Commun. 6(4), 13–18 (1999). https://doi.org/10.1109/98.788210
T. Yuceka, H. Arsalan, A survey of spectrum sensing algorithms for cognitive radio applications. Commun. Surv. Tutor. 11(1), 116–130 (2009). https://doi.org/10.1109/surv.2009.090109
H. Semlali, N. Boumaaz, A. Soulmani, A. Ghammaz, J.F. Diouris, Energy detection approach for spectrum sensing in cognitive radio systems with the use of random sampling. Wirel. Pers. Commun. 79(2), 1053–1061 (2014). https://doi.org/10.1007/s11277-014-1917-6
L. Claudino, T. Abrão, Spectrum sensing methods for cognitive radio networks: a review. Wirel. Pers. Commun. 95(4), 5003–5037 (2017). https://doi.org/10.1007/s11277-017-4143-1
D. Cabric, A. Tkachenko, R.W. Brodersen, Experimental study of spectrum sensing based on energy detection and network cooperation, in Proceedings of the 1st International Workshop on Technology and Policy for Accessing Spectrum (TAPAS ‘06), (ACM, New York, August 2006). https://doi.org/10.1145/1234388.1234400
D. Cabric, S.M. Mishra, R.W. Brodersen, Implementation issues in spectrum sensing for cognitive radios, in Asilomar Conference on Signal, Systems and Computers, November 2004, https://doi.org/10.1109/acssc.2004.1399240
I. Bilinskis, A. Mikelsons, Randomized Signal Processing (Prentice Hall, Cambridge, 1992)
J.J. Wojtiuk, Randomized sampling for radio design, Ph.D. thesis, University of South Australia, School of Electrical and Information Engineering, Australia, 2000
A. Bjorck, Numerical Methods for Least Squares Problems (SIAM, Philadelphia, PA, 1996)
Gnu radio – the free and open software radio ecosystem [Online], Available: http://gnuradio.org/
H.S. Shapiro, R.A. Silverman, Alias-free sampling of random noise. SIAM J. Appl. Math. 8, 225–236 (1960)
K.G. Smitha, A.P. Vinod, R. Prashob, Low power DFT filter bank based two-stage spectrum sensing, in 2012 International Conference on Innovations in Information Technology, 2012, https://doi.org/10.1109/innovations.2012.6207725
D. Kakkar, A. Khosla, M. Uddin, Performance evaluation of energy detection in spectrum sensing for cascaded multihop networks over Nakagami-n fading channel. Int. J. Grid Distrib. Comput. 6(5), 61–70 (2013)
F.F. Digham, M.-S. Alouini, M.K. Simon, On the energy detection of unknown signals over fading channels. IEEE Trans. Commun. 55(1), 21–24 (2007)
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Semlali, H., Boumaaz, N., Maali, A., Soulmani, A., Ghammaz, A., Diouris, JF. (2019). Exploring the Application of Random Sampling in Spectrum Sensing. In: Woungang, I., Dhurandher, S. (eds) 2nd International Conference on Wireless Intelligent and Distributed Environment for Communication. WIDECOM 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-030-11437-4_11
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DOI: https://doi.org/10.1007/978-3-030-11437-4_11
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