Skip to main content
SpringerLink
Log in

A Proposed Scheme for Dynamic Threshold Versus Noise Uncertainty in Cognitive Radio Networks (DTNU)

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Cognitive radio essentially depends on optimum spectrum sensing for primary user detection. Noise uncertainty in spectrum sensing makes the detection process with fixed threshold unreliable due to thermal noise and interference from other remote communication systems, which in turn results in variation in the signal to noise ratio (SNR). In this paper, a dynamic detection threshold under noise uncertainty scheme is proposed for spectrum sensing to improve the detection performance in an environment characterized with noise uncertainty and low SNR. Hence, the detection threshold at each secondary user is dynamically changing according to the predefined detection and false alarm probabilities together with the received SNR at each node. Furthermore, our proposed integrated algorithm aims at finding the targeted number of samples, sensing time and user’s throughput, while maintaining the detection performance metrics within the desired thresholds. A derived mathematical model and computer simulations are provided to show the influence of the dynamic threshold on system performance, and proof the robustness of our proposed scheme under noise uncertainty environment. Our results show a considerable reduction in number of sensed samples (up to 27%) compared to the approach in literature under low SNR.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Chen, D., Li, J., & Ma, J. (2008). Cooperative spectrum sensing under noise uncertainty in cognitive radio. In WiCOM ‘08. 4th international conference (pp. 1–4).

  2. Chabbra, K., Mahendru, G., & Banerjee, P. (2014). Effect of dynamic threshold & noise uncertainty in energy detection spectrum sensing technique for cognitive radio systems. In International conference on signal processing and integrated networks (SPIN) (pp. 377–381).

  3. Liu, F., Wang, J., & Han, Y. (2013). An adaptive double thresholds scheme for spectrum sensing in cognitive radio networks. In IEEE international conference, (ICSPCC) (pp. 1–5).

  4. El-Saleh, A., Ismail, M., Ali, M., Kamarudin, M. R., & Rahman, T. A. (2011). Analytical simulation and performance optimization for spectrum sensing in cognitive radio networks. International Journal on Computer Science and Engineering (IJCSE), 3(2), 554–568.

    Google Scholar 

  5. Liang, Y., Zeng, Y., Peh, E., & Hoang, A. (2008). Sensing-throughput tradeoff for cognitive radio networks. IEEE Transactions on Wireless Communications, 7, 1326–1337.

    Article  Google Scholar 

  6. Cabric, D., Tkachenko, A., & Brodersen, R.W. (2006). Experimental study of spectrum sensing based on energy detection and network cooperation. In Proceeding of the first international workshop on technology and policy for accessing spectrum, Article No. 12.

  7. Yu, G., Long, C., & Xiang, M. (2012). A novel spectrum detection scheme based on dynamic threshold in cognitive radio systems. Research Journal of Applied Sciences, Engineering and Technology, Maxwell Scientific Organization, 4(21), 4245–4251.

    Google Scholar 

  8. Maleki, S., Prabhakar, S., & Leus, G. (2011). Energy and throughput efficient strategies for cooperative spectrum sensing in cognitive radios. In IEEE 12th international workshop on signal processing advances in wireless communications (SPAWC) (pp. 71–75).

  9. Shen, J., Liu, S., Zhang, R., & Liu, Y. (2008). Soft versus hard cooperative energy detection under low SNR. In IEEE, international conference on communications and networking, China, CHINACOM (pp. 128–131).

  10. Hoseini, P., & Beaulieu, N. (2010). An optimal algorithm for wideband spectrum sensing in cognitive radio systems. In IEEE ICC (pp. 1–6).

  11. Althunibat, S., Palacios, R., & Granelli, F. (2012). Energy-efficient spectrum sensing in cognitive radio networks by coordinated reduction of the sensing users. In IEEE international conference on communications (ICC) (pp. 1399–1404).

  12. Zhuan, Y., Memik, G., & Grosspietsch, J. (2008). Energy detection using estimated noise variance for spectrum sensing in cognitive radio networks. In WCNC proceedings (pp. 711–716).

  13. Yu, G., Long, C., & Xiang, M. (2012). Research on dynamic threshold based energy detection in cognitive radio systems. Advanced Materials Research, 462, 506–511.

    Article  Google Scholar 

  14. Kim, H., & Shin, K. G. (2010). In-band spectrum sensing in IEEE 802.22 WRANs for incumbent protection. IEEE Transactions on Mobile Computing, 9(12), 1766.

    Article  Google Scholar 

  15. Second Report and Order and Memorandum Opinion and Order 08-260. (2008). p. 103.

  16. El-Saleh, A., Ismail, M., Ali, M., & Alnuaimy, A. (2009). Capacity optimization for local and cooperative spectrum sensing in cognitive radio networks. World Academy of Science, Engineering and Technology, 4, 679.

    Google Scholar 

  17. Yeow, E. C., Liang, Y. C., Guan, Y. L., & Zeng, Y. (2009). Optimization of cooperative sensing in cognitive radio networks: A sensing-throughput tradeoff view. IEEE Transactions on Vehicular Technology, 58(9), 5294–5299.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Science and Technology, Hebron University, Hebron, Palestine

    Adnan M. Arar

  2. Faculty of Engineering and Information Technology, An-Najah National University, Nablus, Palestine

    Ahmed M. Masri & Hidaya O. Ghannam

  3. Faculty of Engineering and Technology, Birzeit University, Birzeit, Palestine

    Iyad K. Tumar

Authors
  1. Adnan M. Arar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ahmed M. Masri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hidaya O. Ghannam
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Iyad K. Tumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adnan M. Arar.

Ethics declarations

Conflict of Interest

The authors declare that no conflict of interest exists in publishing this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arar, A.M., Masri, A.M., Ghannam, H.O. et al. A Proposed Scheme for Dynamic Threshold Versus Noise Uncertainty in Cognitive Radio Networks (DTNU). Wireless Pers Commun 96, 4543–4555 (2017). https://doi.org/10.1007/s11277-017-4402-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4402-1

Keywords

Search

Navigation