Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Throughput maximization with reduced data loss rate in cognitive radio network

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

In this paper, we have investigated a technique to eliminate the sensing-throughput trade-off of the conventional method in the cognitive radio network. First, we have discussed the sensing—throughput trade-off caused by the conventional method in the cognitive radio network and then proposes a frame structure for eliminating such an issue which is presented in the conventional approach. However, the proposed method has a drawback, which is solved by the enhancement in the frame structure. We have numerically simulated and compared the throughput of cognitive users for both (conventional and propose) methods. The frame structure enhancement technique decreases the probability of frame collision between the primary and secondary users (SUs) and reduces the data rate loss.

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

Access this article

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Computer Networks, 50(13), 2127–2159.

    Article  Google Scholar 

  2. Akyildiz, I. F., Lee, W.-Y., & Chowdhury, K. R. (2009). CRAHNs: cognitive radio ad hoc networks. Ad Hoc Networks, 7(5), 810–836.

    Article  Google Scholar 

  3. Badoi, C.-I., Prasad, N., Croitoru, V., & Prasad, R. (2011). 5G based on cognitive radio. Wireless Personal Communications, 57, 441–464.

    Article  Google Scholar 

  4. Federal Communications Commission, Spectrum policy task force report, FCC 02-155, Nov. 2002.

  5. 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 

  6. Jandral, F. K. (2005). Software defined radio-basics and evolution to cognitive radio. EURASIP Journal on Wireless Communications and Networking, 3, 275–283.

    Google Scholar 

  7. Kay, S. M. (1998). Fundamentals of statistical signal processing: detection theory (Vol. 2. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  8. Kapoor, S., & Singh, G. (2011). Non-cooperative spectrum sensing: a hybrid model approach. In Proc. of int. conf. on devices and communications (ICDeCom-11), India, 24–25 Feb. (pp. 1–5).

    Google Scholar 

  9. Kang, X., Liang, Y.-C., Garg, H. K., & Zhang, L. (2009). Sensing-based spectrum sharing in cognitive radio networks. IEEE Transactions on Vehicular Technology, 58(8), 4649–4654.

    Article  Google Scholar 

  10. Liang, Y.-C., Zeng, Y., Peh, E., & Hoang, A. T. (2007). Sensing-throughput trade-off for cognitive radio networks. In Proc. of IEEE international conference on communications (ICC 2007), Glasgow, June 2007 (pp. 5330–5335).

    Chapter  Google Scholar 

  11. Liang, Y.-C., Zeng, Y., Peh, E. C. Y., & Hoang, A. T. (2008). Sensing-throughput trade-off for cognitive radio networks. IEEE Transactions on Wireless Communications, 7(4), 1326–1337.

    Article  Google Scholar 

  12. Mitola, J., & Maguire, G. Q. (1999). Cognitive radio: making software radio more personal. IEEE Personal Communications, 6(4), 13–18.

    Article  Google Scholar 

  13. Navaie, K. (2011). On the interference management in wireless multi-user network. Telecommunication Systems, 46, 135–148.

    Article  Google Scholar 

  14. Poor, H. V. (1998). An introduction to signal detection and estimation (2nd ed.). New York: Springer.

    Google Scholar 

  15. Singh, G. (2011). Optimization of spectrum management issues for cognitive radio. Journal of Emerging Technologies in Web Intelligence, 3(4), 263–267. (Invited paper).

    Article  Google Scholar 

  16. Stotas, S., & Nallanathan, A. (2010). Overcoming the sensing-throughput tradeoff in cognitive radio networks. In Proc. of IEEE international conference on communication (ICC), Cape Town, 23–27 May 2010 (pp. 1–5).

    Google Scholar 

  17. Stotas, S., & Nallanathan, A. (2010). On the throughput maximization of spectrum sharing cognitive radio networks. In Proc. of IEEE. global telecommunications conference (GLOBECOM 2010), Miami, FL, 6–10 Dec 2010 (pp. 1–5).

    Google Scholar 

  18. Tang, L., et al. (2011). Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks. Telecommunication Systems. doi:10.1007/s11235-011-9486-4.

    Google Scholar 

  19. Tang, Z., Wei, G., & Zhu, Y. (2009). Weighted sum rate maximization for OFDM-based cognitive radio systems. Telecommunication Systems, 42, 77–84. doi:10.1007/s11235-009-9170-0.

    Article  Google Scholar 

  20. Tzeng, S.-S., & Huang, C.-W. (2011). Effective throughput maximization for in-band sensing and transmission in cognitive radio networks. Wireless Networks, 17, 1015–1029.

    Article  Google Scholar 

  21. Zhang, Y., & Leung, C. (2009). Cross-layer resource allocation for real-time services in OFDM-based cognitive radio systems. Telecommunication Systems, 42, 97–108.

    Article  Google Scholar 

  22. Zhao, Q., & Swami, A. (2007). A decision-theoretic framework for opportunistic spectrum access. IEEE Wireless Communications, 14(4), 14–20.

    Article  Google Scholar 

  23. Zhu, J., Wang, J., Luo, T., & Li, S. (2009). Adaptive transmission scheduling over fading channels for energy-efficient cognitive radio networks by reinforcement learning. Telecommunication Systems, 42, 123–138.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. Singh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pandit, S., Singh, G. Throughput maximization with reduced data loss rate in cognitive radio network. Telecommun Syst 57, 209–215 (2014). https://doi.org/10.1007/s11235-013-9858-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-013-9858-z

Keywords

Navigation