Cooperative Spectrum Sensing In Cognitive Radio Networks and Minimization of Error Probability Using Optimal Decision Voting Rule

P. Venkatramana*, S. Narayana Reddy**
*-** Sree Vidyanikethan Engineering College, Department of ECE, Tirupati, Andhra Pradesh, India.
Periodicity:July - September'2014
DOI : https://doi.org/10.26634/jdp.2.3.3012

Abstract

To solve the conflicts between spectrum scarcity and spectrum under-utilization, cognitive radio (CR) technology has been recently proposed. It can improve the spectrum utilization by allowing secondary networks (users) to make use of unused radio spectrum from primary licensed networks (users) or to share the spectrum with the primary networks (users). As an intelligent wireless communication system, a cognitive radio is sentient of the radio frequency environment. It selects the communication parameters such as carrier frequency, bandwidth, and transmission power to optimize the spectrum usage and adapts its transmission and reception accordingly. Cooperative spectrum sensing is considered where multiple cognitive radios detect the spectrum holes collaboratively through energy detection and examine the optimality of cooperative spectrum sensing. The aim is to optimize the detection per-formance in an efficient way. The optimal voting rule is derived for any detector functional to cooperative spectrum sensing. Also optimize the detection threshold when energy detection is in use. To conclude, we propose a spectrum sensing algorithm for the network which requires smaller quantity than the total number of cognitive radios in cooperative spectrum sensing while fulfilling a given error hurdle.

Keywords

Spectrum Sensing, Cognitive Radio, Energy Detection, Optimizatal Detection, Total Error Rate, AND Rule, OR Rule.

How to Cite this Article?

Venkatramana.P. and Reddy,N.S. (2014). Cooperative Spectrum Sensing In Cognitive Radio Networks and Minimization of Error Probability Using Optimal Decision Voting Rule. i-manager’s Journal on Digital Signal Processing, 2(3), 22-27. https://doi.org/10.26634/jdp.2.3.3012

References

[1]. Rui Zhang, Ying-Chang Liang, and Shuguang Cui (2010). “Dynamic Resource Allocation in Cognitive Radio Networks”, IEEE Signal Processing Magazine, pp. 102-114.
[2]. Ying-Chang Liang, Kwang-Cheng Chen, Ye (Geoffrey) Li, Petri Mahonen, (2011). “Advances in Cognitive Radio Networking and Communications” IEEE Journal on Selected Areas in Communications, Vol. 29, No. 4, pp. 673- 675.
[3]. F. F. Digham, M.-S. Alouini, and M. K. Simon, (2003). “On the Energy Detection of Unknown Signals over Fading Channels," IEEE International Conference on Communication (ICC'03), Anchorage, AK, USA, pp. 3575- 3579.
[4]. Vehbi Cagri Gungor and Dilan Sahin, (2012). “Cognitive Radio Networks for Smart Grid Applications”, IEEE Vehicular Technology Magazine, pp. 41-46.
[5]. W. Zhang and K. B. Letaief, (2008). “Cooperative Spectrum Sensing with Transmit and Relay Diversity in Cognitive Radio Networks," IEEE Trans. Wireless Commun., Vol. 7, pp. 4761-4766, Dec.
[6]. K. B. Letaief and W. Zhang, (2009). “Cooperative Communications for Cognitive Radio," Proc. IEEE, Vol. 97, No. 5, pp. 878-893.
[7]. Federal Communications Commission, (2002). “Spectrum Policy Task Force," Rep. ET docket No. 02-135, Nov.
[8]. J.Mitola and G. Q. Maguire, (1999). “Cognitive Radio: Making Software Radios More Personal," IEEE Personal Commun., Vol. 6, pp. 13-18, Aug.
[9] G. Ganesan and Y. G. Li, (2005). “Cooperative Spectrum Sensing in Cognitive Radio Networks," in Proc. IEEE Symp. New Frontiers Dynamic Spectrum Access Networks (DySPAN'05), Baltimore, USA, Nov., pp. 137-143.
[10]. S. M. Mishra, A. Sahai, and R. Brodersen, (2006). “Cooperative Sensing among Cognitive Radios IEEE International Conference on Communication. (ICC'06), Turkey, Vol. 4, pp. 1658-1663.
[11]. D. Cabric, S. M. Mishra, and R. W. Brodersen, (2004). “Implementation Issues in Spectrum Sensing for Cognitive Radios," in Proc. Asilomar Conf. Signals, Systems, Computers, Nov. 2004, Vol. 1, pp. 772-776.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.