Abstract
With the rapid development of wireless communications technology, the problem of scarcity of spectrum resources is becoming serious. Cognitive radio (CR) which is an effective technology to improve the utilization of spectrum resources is getting more and more attention. Spectrum sensing is a key technology in cognitive radio. Wideband spectrum sensing (WBSS) can help secondary users (SUs) find more spectrum holes. However, for the traditional energy detection (ED) algorithm, when the signal-to-noise ratio (SNR) of the primary user (PU) is low, the detection performance is extremely poor owing to the single frequency point detection method. Therefore, the concept of spectrum correlation is proposed. Spectrum correlation algorithm uses the detection window to realize joint detection of multiple frequency points which can improve performance. This paper focuses on how to make the best of spectrum correlation to ensure the detection performance for low SNR signals. We propose an adaptive detection window (ADW) method, whose detection window is adaptively selected based on the estimated SNR of signal. The method can be directly used for wideband spectrum sensing when the approximate position of each signal and its estimated SNR are known. In this context, to show the robustness of the ADW method, a simulation of the sensitivity of the ADW method to the SNR estimation error is performed. Meanwhile, simulations of methods comparison demonstrate that the proposed ADW method outperforms the commonly used iterative energy detection method, frequency correlation methods and histogram-based segmentation method by far.
This work is supported in part by the National Natural Science Foundation of China (No. 61631004) and the National Science and Technology Major Project of China under Grant 2016ZX03001017.
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References
Facilitating Opportunities for Flexible, Efficient, and Reliable Spe ctrum Use Employing Cognitive Radio Technologies, FCC 03–322. Federal Commun. Commission, Washington, DC, USA, December 2003
Haykin, S.: Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)
Mitola, J., Maguire, G.Q.: Cognitive radio: making software radios more personal. IEEE Pers. Commun. 6(4), 13–18 (1999)
Yucek, T., Arslan, H.: A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun. Surv. Tutor. 11(1), 116–130 (2009)
Mariani, A., Giorgetti, A., Chiani, M.: Effects of noise power estimation on energy detection for cognitive radio applications. IEEE Trans. Commun. 59(12), 3410–3420 (2011)
Hwang, J., Chang, W., Hu, P.: A sub-nyquist wideband spectrum sensing scheme using aliased spectral edge detection and database matching. In: 2015 International Conference on Wireless Communications and Signal Processing (WCSP), Nan**g, pp. 1–5 (2015)
Quan, Z., Cui, S., Sayed, A.H., Poor, H.V.: Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Trans. Signal Process. 57(3), 1128–1140 (2009)
Bao, D., De Vito, L., Rapuano, S.: A histogram-based segmentation method for wideband spectrum sensing in cognitive radios. IEEE Trans. Instrum. Meas. 62(7), 1900–1908 (2013)
Yuan, L., Ren, F., **ng, L., Peng, T., Wang, W.: Wideband spectrum sensing algorithm based on frequency correlation. In: 2013 15th IEEE International Conference on Communication Technology, Guilin, pp. 211–217 (2013)
Gahane, L., Sharma, P.K., Varshney, N., Tsiftsis, T.A., Kumar, P.: An improved energy detector for mobile cognitive users over generalized fading channels. IEEE Trans. Commun. 66(2), 534–545 (2018)
Ziyang, L., Tao, P.: Energy detection about broadband signal without priori information of interference system. J. Bei**g Univ. Posts Telecommun. 35(5), 31–35 (2012)
Bhowmick, A., Chandra, A., Roy, S.D., Kundu, S.: Double threshold-based cooperative spectrum sensing for a cognitive radio network with improved energy detectors. IET Commun. 9(18), 2216–2226 (2015)
Wang, X., Peng, T., Wang, W.: Low-SNR energy detection based on relevance in power density spectrum. In: Liang, Q., Mu, J., Wang, W., Zhang, B. (eds.) Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems. LNEE, vol. 386, pp. 283–291. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49831-6_29
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Lan, B., Peng, T., Zuo, P., Wang, W. (2020). A Novel Spectrum Correlation Based Energy Detection for Wideband Spectrum Sensing. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_17
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