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Performance of Energy Detector for Cognitive Radio System over AWGN and Rayleigh Channel

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Buthaina Mosa, Aya Falah Algamluoli

Buthaina Mosa and Aya Falah Algamluoli. Performance of Energy Detector for Cognitive Radio System over AWGN and Rayleigh Channel. International Journal of Computer Applications 167(3):30-34, June 2017. BibTeX

	author = {Buthaina Mosa and Aya Falah Algamluoli},
	title = {Performance of Energy Detector for Cognitive Radio System over AWGN and Rayleigh Channel},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {3},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {30-34},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914220},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Cognitive radio has a critical application which it is Spectrum access, and knowing that the key to this application is detected in the spectrum to find free bands. Nowadays the studies confirmed that the energy detector methods are the most convenient method. In this work, we present the energy detector and explain how it is a convenient method in a sense because it doesn't need any prior information about the primary user. The simulation of energy detection methods has been done in MATLAB program, for both, AWGN and Rayleigh channels. The simulation confirmed the theoretical results, which gives that the performance of AWGN channel is greater than a Rayleigh channel, it is also verified that the performance of the detector is independent of the type of modulation.


  1. Abdessamad, E., Saadane, R., El Aroussi, M., Wahbi, M., & Hamdoun, A. (2014, April). Spectrum sensing with an improved Energy detection. In Multimedia Computing and Systems (ICMCS), 2014 International Conference on (pp. 895-900). IEEE.‏
  2. Wang, W. (2009). Cognitive radio systems. 1st ed. SL:
  3. Yucek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE communications surveys & tutorials, 11(1), 116-130.
  4. Kamil, N. H., & Yuan, X. (2010). Detection proposal schemes for spectrum sensing in cognitive radio. Wireless Sensor Network, 2(05), 365.‏
  5. Zayen, B., Hayar, A., Debbabi, H., & Besbes, H. (2009, October). Application of smoothed estimators in spectrum sensing technique based on model selection. In Ultra Modern Telecommunications & Workshops, 2009. ICUMT'09. International Conference on (pp. 1-4). IEEE.‏
  6. Umar, R., & Sheikh, A. U. (2013). A comparative study of spectrum awareness techniques for cognitive radio oriented wireless networks. Physical Communication, 9, 148-170.
  7. Ariananda, D. D., Lakshmanan, M. K., & Nikookar, H. (2009, May). A survey on spectrum sensing techniques for cognitive radio. In Cognitive Radio and Advanced Spectrum Management, 2009. CogART 2009. Second International Workshop on (pp. 74-79). IEEE.‏
  8. Wyglinski, A., Nekovee, M. and Hou, Y. (2010). Cognitive radio communications and networks. 1st ed. Amsterdam: Elsevier.
  9. Ghasemi, A., & Sousa, E. S. (2005, November). Collaborative spectrum sensing for opportunistic access in fading environments. In New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005. 2005 First IEEE International Symposium on (pp. 131-136). IEEE.‏
  10. Yue, W. J., Zheng, B. Y., Meng, Q. M., & Yue, W. J. (2010). Combined energy detection and one-order cyclostationary feature detection techniques in cognitive radio systems. The Journal of China Universities of Posts and Telecommunications, 17(4), 18-25.‏
  11. Cabric, D., Tkachenko, A., & Brodersen, R. W. (2006, August). Experimental study of spectrum sensing based on energy detection and network cooperation. In Proceedings of the first international workshop on Technology and policy for accessing spectrum (p. 12). ACM.‏
  12. Ranjeeth, M., & Anuradha, S. (2015). Performance of Fading Channels on Energy Detection Based Spectrum Sensing. Procedia Materials Science, 10, 361-370.‏


Cognitive radio, spectrum sensing, energy detection, AWGN channel, Rayleigh channel, probability of detection, probability of false alarm.