A Comparative Study of Different Entropies for Spectrum Sensing Techniques
In this paper, we propose entropy-based spectrum sensing schemes to detect the existence of a primary user in Cognitive Radio (CR). To support this proposal, we have studied four types of entropies [Approximate Entropy (ApEn), Bispectral Entropy (BispEn), Sample Entropy (SamEn) and Rényi Entropy (Re...
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| Published in | Wireless personal communications Vol. 69; no. 4; pp. 1719 - 1733 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Springer US
01.04.2013
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| Abstract | In this paper, we propose entropy-based spectrum sensing schemes to detect the existence of a primary user in Cognitive Radio (CR). To support this proposal, we have studied four types of entropies [Approximate Entropy (ApEn), Bispectral Entropy (BispEn), Sample Entropy (SamEn) and Rényi Entropy (RenyiEn)] and their applications for spectrum sensing. The reason for investigating these entropies comes from the fact that different types of entropies have different characteristics which make them more or less suitable for specific applications. Monte Carlo simulations were executed to find out how suitable these measures are for CR. Averaged value curves, boxplots and Analysis of Variance (ANOVA) tests document the performance of these types of entropies. The results show that BispEn outperformed the other three entropy measures. The ANOVA test shows that BispEn can sense modulated signals when the (SNR) is as low as −15 dB. This is at least a 5 dB improvement compared to the other entropies studied in this paper. |
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| AbstractList | In this paper, we propose entropy-based spectrum sensing schemes to detect the existence of a primary user in Cognitive Radio (CR). To support this proposal, we have studied four types of entropies [Approximate Entropy (ApEn), Bispectral Entropy (BispEn), Sample Entropy (SamEn) and Rényi Entropy (RenyiEn)] and their applications for spectrum sensing. The reason for investigating these entropies comes from the fact that different types of entropies have different characteristics which make them more or less suitable for specific applications. Monte Carlo simulations were executed to find out how suitable these measures are for CR. Averaged value curves, boxplots and Analysis of Variance (ANOVA) tests document the performance of these types of entropies. The results show that BispEn outperformed the other three entropy measures. The ANOVA test shows that BispEn can sense modulated signals when the (SNR) is as low as −15 dB. This is at least a 5 dB improvement compared to the other entropies studied in this paper. In this paper, we propose entropy-based spectrum sensing schemes to detect the existence of a primary user in Cognitive Radio (CR). To support this proposal, we have studied four types of entropies [Approximate Entropy (ApEn), Bispectral Entropy (BispEn), Sample Entropy (SamEn) and RACOnyi Entropy (RenyiEn)] and their applications for spectrum sensing. The reason for investigating these entropies comes from the fact that different types of entropies have different characteristics which make them more or less suitable for specific applications. Monte Carlo simulations were executed to find out how suitable these measures are for CR. Averaged value curves, boxplots and Analysis of Variance (ANOVA) tests document the performance of these types of entropies. The results show that BispEn outperformed the other three entropy measures. The ANOVA test shows that BispEn can sense modulated signals when the (SNR) is as low as ?15 dB. This is at least a 5 dB improvement compared to the other entropies studied in this paper. |
| Author | Faust, Oliver Ma, Jianguo Zhu, Wanjing |
| Author_xml | – sequence: 1 givenname: Wanjing surname: Zhu fullname: Zhu, Wanjing email: wjzhu@uestc.edu.cn organization: School of Electronic Engineering, University of Electronic Science and Technology of China – sequence: 2 givenname: Jianguo surname: Ma fullname: Ma, Jianguo organization: School of Electronic Information Engineering, Tianjin University – sequence: 3 givenname: Oliver surname: Faust fullname: Faust, Oliver organization: School of Engineering, Ngee Ann Polytechnic |
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| Cites_doi | 10.1109/SURV.2009.090109 10.1109/LSP.2009.2016014 10.1109/LCOMM.2010.06.091954 10.1109/PROC.1987.13824 10.1063/1.166092 10.1109/TBME.2006.889772 10.1109/JSAC.2004.839380 10.1016/0165-1684(89)90081-9 10.1016/j.bpa.2005.07.009 10.1017/S0080456800012163 10.1007/s11277-008-9473-6 10.1049/iet-com.2009.0389 10.1007/s11277-008-9465-6 10.1016/j.sigpro.2008.07.022 10.1016/j.cmpb.2010.07.011 10.1007/s11277-011-0239-1 10.1016/j.bspc.2011.06.002 10.1109/MILCOM.2006.302553 10.1109/ICSMC.2010.5642249 10.1002/j.1538-7305.1948.tb01338.x 10.21437/Eurospeech.2001-446 10.1152/ajpheart.2000.278.6.H2039 10.1109/WTS.2008.4547544 |
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| Keywords | Cognitive radio Entropy Spectrum sensing Monte Carlo method Variance analysis Modeling Spectral analysis Variance Channel estimation Wireless network Value analysis Software radio Signal to noise ratio Information theory |
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| Title | A Comparative Study of Different Entropies for Spectrum Sensing Techniques |
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