Performance Analysis of the Time-Based and Periodogram-Based Energy Detector for Spectrum Sensing
Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1130657Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 819
 E. H. Gismalla and E. Alsusa, “Performance Analysis of the Periodogram-based Energy Detector in Fading Channels”, IEEE Transactions on Signal Processing, vol 59, no 8, August 2011.
 J. Mitola and G.Q. Maguire, “Cognitive radio: making software radios more personal,”IEEE Personal Communications, vol. 6, pp. 13–18, August 1999.
 A. Sonnenschein and P. M. Fishman,“Radiometric detection of spreadspectrum signals in noise of uncertainty power,” IEEE Transactions on Aerospace and Electronic Systems, vol. 28, no. 3, pp. 654–660, 1992.
 A. Sahai and D. Cabric, “Spectrum sensing: fundamental limits and practical challenges,” IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’05), Baltimore, Md, USA, November 2005.
 W. A. Gardner, “Exploitation of spectral redundancy in cyclostationary signals,” IEEE Signal Processing Magazine, vol. 8, no. 2, pp. 14–36, 1991.
 Y. H. Zeng and Y.-C. Liang, “Eigenvalue-based spectrum sensing algorithms for cognitive radio,” IEEE Transactions on Communications, vol. 57, no. 6, pp. 1784–1793, 2009.
 Y. H. Zeng and Y.-C. Liang, “Covariance based signal detections for cognitive radio,” in Proceedings of the 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’07), pp. 202–207, Dublin, Ireland, April 2007.
 S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, vol. 2, Prentice Hall, Upper Saddle River, NJ, USA, 1998.
 H. S. Chen, W. Gao, and D. G. Daut, “Signature based spectrum sensing algorithms for IEEE 802.22 WRAN,” in Proceedings of the IEEE International Conference on Communications (ICC ’07), pp. 6487–6492, Glasgow, Scotland, June 2007.
 Sepideh Zarrin, “Spectrum Sensing in Cognitive Radio Networks”, PHD thesis, University of Toronto, 2011.
 N. Han, S. H. Shon, J. O. Joo, and J. M. Kim, “Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems,” in Proceedings of the 8th International Conference on Advanced Communication Technology, Phoenix Park, South Korea, Febraury 2006.
 H. Urkowitz, “Energy detection sof unkown deterministic signals,” Proceedings of the IEEE, vol. 55, no. 4, pp. 523–531,1967.
 E. Alsusa and E.H. Gismalla, “An Accurate Model For Periodogram-Based Energy Detection Over Nakagami Fading”, IEEE International Conference on Communications (ICC), pp 1614 – 1618, June 2012.
 D. Cabric, A. Tkachenko and R. W. Brodersen, “Experimental Study of Spectrum Sensing Based on Energy Detection and Network Cooperation”, TAPAS '06 Proceedings of the First International Workshop on Technology and Policy for Accessing Spectrum, Article No 12, 2006.
 F. F. Digham, M. Alouini and M. K. Simon, “On The Energy Detection of Unknown Signals Over Fading Channels”, IEEE Transactions on Communications, Vol 55, No 1, January 2007.
 N. Reisi, M. Ahmadian and S. Salari, “Performance Analysis of Energy Detection Based Spectrum Sensing Over Fading Channels”, WiCOM, pp 1-4, 2010.
 I. S. Gradshteyn and I. M. Ryzhik, “Table of Integrals, Series, and Products”, 5th ed. Academic Press, 1994.
 A. H. Nuttall, “Some Integrals Involving The QM Function”, IEEE Transactions on Information Theory, Vol. 21, No. 1, pp. 95-96, January 1975.
 HJ. G. Proakis, Digital Communications, 4th ed, pp 49-53.
 A. D. Polyanin and A. V. Manzhirov, Handbook of Mathematics for Engineers and Scientists, Chapman and Hall, pp1056.
 Haiyun Tang, “Some Physical Layer Issues of Wide-band Cognitive Radio Systems”, IEEE New Frontiers in Dynamic Spectrum Access Networks, pp. 151-159, 2005.
 W. Brye, “Normal Distributions” in Normal Distribution Characterizations with Applications, 1st ed. Berlin: Springer, 1995, pp. 19-20.