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

Advertisement

Springer Nature Link
Log in

A Comprehensive Analysis of Energy Efficiency Using Cooperative Spectrum Sensing Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The proposed cooperative spectrum sensing network presented in this paper has potential properties that could improve the detection probability. The proposed network consists of multiple cognitive radio (CR) nodes. Each CR node is equipped with several antennas, and selection combining is used to identify the highest value of sensing data associated with each antenna. Further, this sensing data is passed to fusion center and primary user activity is identified at the fusion centre using the fusion rules. This study mainly focuses on identifying unknown signals in a Rayleigh fading environment using an improved energy detector. Initially, the novel analytical closed-form of expressions for false alarm and missing detection probabilities was provided under Rayleigh fading with multiple antennas at each CR. Further, the performance of the total error rate is studied under single and multiple antenna scenarios, and a quantitative evaluation is offered to determine average throughput and energy efficiency performance. Later, to simulate the performance with a solid foundation of mathematical analysis, a simulation test-bed is created in MATLAB. Finally, the performance is improved with the proposed scheme compared to conventional scheme.

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
Fig. 15

Similar content being viewed by others

Data and Material Availability

Data sharing not applicable to this article as no datasets were generated during the current study.

Code Availability

Software Application.

References

  1. Chuah, M. C., & Zhang, Q. (2009). Design and performance of 3G wireless networks and wireless LANS. Springer.

    Google Scholar 

  2. Rehmani, M. H., & Faheem, Y. (2014). Cognitive radio sensor networks: Applications, architectures, and challenges. IGI Publishing.

    Book  Google Scholar 

  3. Osseiran, A., Monserrat, J. F., & Mohr, W. (2011). Mobile and wireless communications for IMT-advanced and beyond. Wiley.

    Book  Google Scholar 

  4. Medeisis, A., & Holland, O. (2014). Cognitive radio policy and regulation. Springer.

    Book  Google Scholar 

  5. Hossain, E., Niyato, D., & Han, Z. (2009). Dynamic spectrum access and management in cognitive radio networks. Cambridge Press.

    Book  Google Scholar 

  6. Khattab, A., Perkins, D., & Bayoumi, M. (2013). Cognitive radio networks from theory to practice. Springer.

    Book  MATH  Google Scholar 

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

    Article  Google Scholar 

  8. Haykin, S. (2005). Cognitive radio brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23(2), 201–220.

  9. Yucek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys & Tutorials, 11(1), 116–130.

    Article  Google Scholar 

  10. Wang, W., Zhang, L., Zou, W., & Zhou, Z. (2007). On the distributed cooperative spectrum sensing for cognitive radio. In International symposium on communication and information technologies (pp. 1496–1501).

  11. Digham, F. F., Alouini, M.-S., & Simon, M. K. (2007). On the energy detection of unknown signals over fading channels. IEEE Trans on Communications, 55, 21–24.

    Article  Google Scholar 

  12. Ganesan, G., & Li, Y., (2007). Cooperative spectrum sensing in cognitive radio, part I: Two user networks. In IEEE trans. on wireless communication (pp. 2204–2213).

  13. Letaief, K. B. (2007). Cooperative spectrum sensing. In E. Hossain & V. K. Bhargava (Eds.), Cognitive wireless communication networks springer. Springer.

    Google Scholar 

  14. Lee, C., & Wolf, W. (2008). Energy efficient techniques for cooperative spectrum sensing in cognitive radios. In IEEE CCNC (pp. 968–972).

  15. Peh, E. C. Y., Liang, Y. C., Guan, Y. L., & Pei, Y. (2011). Energy efficient cooperative spectrum sensing in cognitive radio networks. In Global telecommunications conference (pp. 1–5). IEEE.

  16. Varshney, P. K. (1997). Distributed detection and data fusion. Springer.

    Book  Google Scholar 

  17. Althunibat, S., Narayanan, S., Di Renzo, M., & Granelli, F. (2005). Energy efficient partial-cooperative spectrum sensing in cognitive radio over fading channels. In IEEE VTC spring (pp. 1–5).

  18. Althunibat, S., & Granelli, F. (2014). An objection based collaborative spectrum sensing in cognitive radio networks. IEEE Comminacation Letters, 18(8), 1291–1294.

    Article  Google Scholar 

  19. Althunibat, S., Vuong, T. M., & Granelli, F. (2014). Multi-channel collaborative spectrum sensing in cognitive radio networks. In IEEE 19th international workshop on CAMAD (pp. 234–238).

  20. Maleki, S., Pandharipande, A., & Leus, G. (2011). Energy efficient distributed spectrum sensing for cognitive sensor networks. IEEE Sensors Journal, 11, 565–573.

    Article  Google Scholar 

  21. Zhao, N., Yo, F. R., Sun, H., & Nallanathan, A. (2012). An energy efficient cooperative spectrum sensing scheme for cognitive radio networks. In Global communications conference (pp. 3600–3604).

  22. Shi, Z., Tec, K. C., & Li, K. H. (2013). Energy efficient joint design of sensing and transmission durations for protection of primary user in cognitive radio systems. IEEE Communications Letters, 17, 565–568.

    Article  Google Scholar 

  23. Hang, Hu., Zhang, H., & Yu, H. (2015). Energy-efficient design of channel sensing in cognitive radio networks. Computers and Electrical Engineering, 42, 207–220.

    Article  Google Scholar 

  24. Yadav, K., Prasad, B., Bhowmick, A., Roy, S. D., & Kundu, S. (2017). Throughput performance under primary user emulation attack in cognitive radio networks. International Journal of Communication Systems, 30(18), e3371.

    Article  Google Scholar 

  25. Althunibat, S., Granelli, F. (2014). Energy efficiency analysis of soft and hard cooperative spectrum sensing schemes in cognitive radio networks. In IEEE 79th Vehicular Technology Conference (VTC Spring) (pp. 1–5). Seoul.

  26. Ranjeeth, M., Anuradha, S., & Nallagonda, S. (2020). Optimized cooperative spectrum sensing network analysis in non fading and fading environments. International Journal of Communication Systems, 33(5), e42-62.

    Article  Google Scholar 

  27. Zheng, M., Chen, L., Liang, W., Yu, H., & Wu, J. (2017). Energy-efficiency maximization for cooperative spectrum sensing in cognitive sensor networks. IEEE Transactions on Green Communications and Networking, 1(1), 29–39.

    Article  Google Scholar 

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

    Article  Google Scholar 

  29. Singh, A., Bhatnagar, M. R., & Mallik, R. K. (2016). Performance of an improved energy detector in multihop cognitive radio networks. IEEE Transactions on Vehicular Technology, 65(2), 732–743. https://doi.org/10.1109/TVT.2015.2401332

    Article  Google Scholar 

  30. Digham, F. F., Alouini, S., & Simon, M. K. (2003). On the energy detection of unknown signals over fading channels. In Proceedings of IEEE international conference on communications (ICC’03) (pp. 3575–3579). Alaska, USA.

  31. Chen, Y. (2005). ’Improved energy detector for random signals in Gaussian noise’. IEEE Trans. Wireless. Comm., 9(2), 558–563.

    Article  Google Scholar 

  32. Singh, A., Bhatnagar, M. R., & Mallik, R. K. (2012). Cooperative spectrum sensing in multiple antenna based cognitive radio network using an improved energy detector. IEEE Communications Letters, 16(1), 64–67.

    Article  Google Scholar 

  33. Peh, E. C. Y., 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 

  34. Singh, A., Bhatnagar, M. R., & Mallik, R. K. (2011). Optimization of cooperative spectrum sensing with an improved energy detector over imperfect reporting channel. In Proceedings of IEEE vehicular technology conference (VTC Fall).

  35. Sudhamani, C. (2019). Energy efficiency in cognitive radio network using cooperative spectrum sensing. Wireless Personal Communications, 104, 907–919.

    Article  Google Scholar 

  36. Nallagonda, S., Bhowmick, A., & Prasad, B. (2021). Throughput performance of cooperative spectrum sensing network with improved energy detectors and SC diversity over fading channels. Wireless Networks, 27(6), 4039–4050.

    Article  Google Scholar 

Download references

Funding

The authors received no financial support for the research work.

Author information

Authors and Affiliations

  1. Department of ECE, National Institute of Technology Mizoram, Chatlang, Mizoram, 796 012, India

    Naveen Kumar Boddukuri & Chaitali Koley

  2. Central Electronics Engineering Research Institute, Pilani, Rajasthan, 333031, India

    Debasish Pal & Ayan Kumar Bandyopadhyay

Authors
  1. Naveen Kumar Boddukuri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Debasish Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ayan Kumar Bandyopadhyay
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chaitali Koley
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Naveen Kumar Boddukuri.

Ethics declarations

Conflict of interest

Please check the following as appropriate: All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version. This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue. The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript. The following authors have affiliations with organizations with direct or indirect financial interest in the subject matter discussed in the manuscript:

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Boddukuri, N.K., Pal, D., Bandyopadhyay, A.K. et al. A Comprehensive Analysis of Energy Efficiency Using Cooperative Spectrum Sensing Network. Wireless Pers Commun 129, 641–661 (2023). https://doi.org/10.1007/s11277-022-10123-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-022-10123-3

Keywords

Search

Navigation