Home Energy vs. Cyclostationarity-based Detection of Random Arrival and Departure of LTE SC-FDMA Signals for Cognitive Radio Systems
Article
Licensed
Unlicensed Requires Authentication

Energy vs. Cyclostationarity-based Detection of Random Arrival and Departure of LTE SC-FDMA Signals for Cognitive Radio Systems

  • Ibrahim Atef , Ashraf Eltholth EMAIL logo and M. S. El-Soudani
Published/Copyright: April 9, 2016
Become an author with De Gruyter Brill

Abstract

In cognitive radio systems, the random nature of primary users’ activities heavily influences the performance of spectrum sensing techniques. Considering both of the primary user random arrival and departure in one model is essential for mitigating the performance degradation in spectrum sensing. In this paper, we apply the probability based weighting energy detector (ED) to overcome the effect of random arrival and departure of primary user (PU), on a single carrier-frequency division multiple access (SC-FDMA) signal used in LTE uplink physical channel. Then compare the performance of weighted ED to the second order Cyclostationarity detector with/without the random arrival and departure of primary user signal during the secondary user’s sensing period. The simulation shows that the weighting ED approaches the performance of Cyclostationarity detector in the normal case, where there are no random activities of primary user signals during the secondary user’s sensing period, with less computational complexity. Moreover, the weighted ED outperforms the Cyclostationarity detector in the case of random arrival and departure of PU.

References

[1] I. Atef, A. Eltholth, A. S. Ibrahim, and M. S. El-Soudani, Energy detection of random arrival and departure of primary user signals in cognitive radio systems, in IEEE EUROCON, 2015.10.1109/EUROCON.2015.7313791Search in Google Scholar

[2] W. A. Jerjawi, Y. A. Eldemerdash, and O. A. Dobre, “Second-order cyclostationarity-based detection of LTE SC-FDMA signals for cognitive radio systems,” IEEE Trans. Instrum. Meas., vol. 64, no. 3, pp. 823–833, March 2015.10.1109/TIM.2014.2357592Search in Google Scholar

[3] S. haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE J. Sel Areas Commun., vol. 23, no. 2, pp. 201–220, Feb. 2005.10.1109/JSAC.2004.839380Search in Google Scholar

[4] T. Yucek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Commun. Surv. Tutorials, vol. 11, no. 1, pp. 116, 130, First Quarter 2009.10.1109/SURV.2009.090109Search in Google Scholar

[5] I. Guvenc, “Statistics of macrocell-synchronous femtocell-asynchronous users-delays for improved femtocell uplink receiver design,” IEEE Commun. Letters, vol. 13, no. 4, pp. 239, 241, April 2009.10.1109/LCOMM.2009.081989Search in Google Scholar

[6] L. Tang, Y. Chen, E. Hines, and M.-S. Alouini, “Performance analysis of spectrum sensing with multiple status changes in primary user traffic,” IEEE Commun. Lett., vol. 16, no. 6, pp. 874–877, June 2012.10.1109/LCOMM.2012.041112.120507Search in Google Scholar

[7] N. C. Beaulieu and Y. Chen, “Improved energy detectors for cognitive radios with randomly arriving or departing primary users,” IEEE Signal Process. Lett., vol. 17, no. 10, pp. 867–870, 2010.10.1109/LSP.2010.2064768Search in Google Scholar

[8] J. -Y. Wu, C. -H. Wang, and T.-Yi. Wang, “Performance analysis of energy detection based spectrum sensing with unknown primary signal arrival time,” IEEE Trans. Commun., vol. 59, no. 7, pp. 1779, 1784, July 2011.10.1109/TCOMM.2011.050211.100146Search in Google Scholar

[9] J. Ma and Ye. Li, A Probability-based spectrum sensing scheme for cognitive radio, IEEE Int. Conf. Commun., 2008. ICC ’08, pp. 3416, 3420, 19–23 May 200810.1109/ICC.2008.642Search in Google Scholar

[10] X. Xie and X. Hu, Improved energy detector with weights for primary user status changes in cognitive radios networks, IEEE 11th Consumer Commun. Netw. Conf. (CCNC), 2014, pp. 53, 58, 10–13 Jan. 2014.10.1155/2014/836793Search in Google Scholar

[11] J.-Y. Wu, P.-H. Huang, T.-Yi. Wang, and V. W. S. Wong. Energy detection based spectrum sensing with random arrival and departure of primary user’s signal, IEEE Globecom Workshops (GC Wkshps), 2013, pp. 380, 384, 9–13 Dec. 2013.10.1109/GLOCOMW.2013.6825017Search in Google Scholar

[12] C. M. Spooner and W. A. Gardner, “The cumulant theory of cyclostationary time-series. II. Development and applications,” IEEE Trans. Signal Process., vol. 42, no. 12, pp. 3409–3429, Dec. 1994.10.1109/78.340776Search in Google Scholar

Received: 2015-10-29
Published Online: 2016-4-9
Published in Print: 2016-5-1

©2016 by De Gruyter

Downloaded on 22.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/freq-2015-0237/html
Scroll to top button