Skip to main content

Advertisement

Springer Nature Link
Log in

Improved Spectrum Sharing (ISS) Scheme for Cognitive Radio Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The double threshold based cognitive radio system is very efficient towards having the high detection probability but lacks in the proper utilization of the confused region between the two thresholds. This paper proposes an improved spectrum sharing (ISS) scheme which does not only provide the higher detection probability but also utilizes the confused region in a productive and risk-free manner. Moreover, the proposed scheme achieves better throughput than the conventional cognitive radio (CCR) system based on the single and double threshold, both. To further achieve the improved results, the proposed system has been analyzed for the case of novel cognitive radio system, where, the obtained results are found beyond the sensing-throughput tradeoff and are better than the CCR system. We have further implemented the ISS scheme under the cooperation of n-out-of-k CRs, this cooperative approach makes the proposed system robust enough towards the hidden terminal problem and “shadowing and fading” effects of the wireless communication channel.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Federal Communications Commission. (2002). Spectrum policy task force report, FCC 02-155.

  2. Mitola, J., & Maguire, G. Q. (1999). Cognitive radio: making software radios more personal. IEEE Personal Communications, 6, 13–18.

    Article  Google Scholar 

  3. Mitola, J. (2000). Cognitive radio: An integrated agent architecture for software defined radio. PhD diss., Royal Inst. Technology, Stockholm, Sweden.

  4. Haykin, S. (2005). Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23, 201–220.

    Article  Google Scholar 

  5. Liang, Y. C., Zeng, Y., et. al. (2007). Sensing throughput tradeoff for cognitive radio networks. In IEEE international conference on communications (ICC) (pp. 5330–5335).

  6. Liang, Y. C., Zeng, Y., et al. (2008). Sensing throughput tradeoff for cognitive radio networks. IEEE Transactions on Wireless Communications, 7(4), 1326–1337.

    Article  Google Scholar 

  7. Stotas, S., & Nallanathan, A. (2010). Overcoming the sensing-throughput tradeoff in cognitive radio networks. In IEEE international conference on communications (ICC) (pp. 1–5). doi: 10.1109/ICC.2010.5502792.

  8. Stotas, S., & Nallanathan, A. (2012). On the throughput and spectrum sensing enhancement of opportunistic spectrum access cognitive radio networks. IEEE Transactions on Wireless Communications, 11(1), 97–101.

    Article  Google Scholar 

  9. Pandit, S., & Singh, G. (2013). Throughput maximization with reduced data loss rate in cognitive radio network. Telecommunication Systems. doi:10.1007/s11235-013-9858-z.

    Google Scholar 

  10. Ghasemi, A., & Sousa, E. S. (2007). Fundamental limits of spectrum-sharing in fading environments. IEEE Transactions on Wireless Communications, 6(2), 649–658.

    Article  Google Scholar 

  11. Musavian, L., & Aissa, S. (2007). Ergodic and outage capacities of spectrum-sharing systems in fading channels. In Proceedings of the IEEE global telecommunications (GLOBECOM) conference (pp. 3327–3331).

  12. Stotas, S., & Nallanathan, A. (2011). Enhancing the capacity of spectrum sharing cognitive radio networks. IEEE Transactions on Vehicular Technology, 60(8), 3768–3779.

    Article  Google Scholar 

  13. Kang, X., et al. (2009). Sensing based spectrum sharing in cognitive radio networks. IEEE Transactions on Vehicular Technology, 58(8), 4649–4654.

    Article  Google Scholar 

  14. Wu, J., et al. (2009). An energy detection algorithm based on double-threshold in cognitive radio systems. In IEEE, 1st international conference on information systems engineering (ICISE) (pp. 493–496). doi: 10.1109/ICISE.2009.257.

  15. Xie, J. Q., & Chen, J. (2012). An adaptive double-threshold spectrum sensing algorithm under noise uncertainty. In IEEE 12th international conference on computer and information technology (CIT) (pp. 824–827). doi: 10.1109/CIT.2012.171.

  16. Liu, S.-Q., et al. (2012). Hierarchical cooperative spectrum sensing based on double thresholds energy detection. IEEE Communications Letters, 16(7), 1096–1099.

    Article  Google Scholar 

  17. Zhu, J., et al. (2008). Double threshold energy detection of cooperative spectrum sensing in cognitive radio. In IEEE, cognitive radio oriented wireless networks and communications (CROWNCOM) (pp. 1–5). doi: 10.1109/CROWNCOM.2008.4562451.

  18. Jafarian, J., & Hamdi, K. A. (2012). Throughput optimization in a cooperative double-threshold sensing scheme. In IEEE, wireless communications and networking (WCNC) (pp. 1034–1038). doi: 10.1109/WCNC.2012.6213925.

  19. Zhang, W., & Lataief, K. B. (2008). Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks. IEEE Transactions on Wireless Communications, 7(12), 4761–4766.

    Article  Google Scholar 

  20. Ghasemi, A., et al. (2005). Collaborative spectrum sensing for opportunistic spectrum access in fading environments. In Proceedings of 1st IEEE international symposium on new frontiers in dynamic spectrum access networks, Baltimore, USA, (pp. 131–136).

  21. Wang, Y., et al. (2014). Optimization of cluster-based cooperative spectrum sensing scheme in cognitive radio networks with soft data fusion. Wireless Personal Communications. doi:10.1007/s11277-014-1673-7.

    Google Scholar 

  22. Sun, C. et al. (2007). Cooperative spectrum sensing for cognitive radios under bandwidth constraints. In Proceedings of IEEE wireless communications and networking conference, Hong Kong, China (pp. 1–5).

  23. Zhang, W., et al. (2009). Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Transactions on Wireless Communications, 8(12), 5761–5766.

    Article  Google Scholar 

  24. Peh, E. C. Y., et al. (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. Electronics and Communication Engineering, National Institute of Technology Kurukshetra (NITKKR), Kurukshetra, Haryana, India

    Gaurav Verma & O. P. Sahu

Authors
  1. Gaurav Verma
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. O. P. Sahu
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Gaurav Verma.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Verma, G., Sahu, O.P. Improved Spectrum Sharing (ISS) Scheme for Cognitive Radio Networks. Wireless Pers Commun 96, 2323–2340 (2017). https://doi.org/10.1007/s11277-017-4300-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4300-6

Keywords