Spectrum Challenges and Solutions by Cognitive Radio: An Overview
Wireless Personal Communications: An International Journal
Cognitive Radio Dynamic Access Techniques
Wireless Personal Communications: An International Journal
Entropy-based spectrum sensing in cognitive radio
Signal Processing
A frequency-domain entropy-based detector for robust spectrum sensing in cognitive radio networks
IEEE Communications Letters
Entropy-based spectral processing on the IEEE 802.11a OFDM waveform
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Spectrum Sensing Framework for Cognitive Radio Networks
Wireless Personal Communications: An International Journal
Computer Methods and Programs in Biomedicine
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Wireless Personal Communications: An International Journal
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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 驴15 dB. This is at least a 5 dB improvement compared to the other entropies studied in this paper.