Skip to main content

Performance of Cooperative Spectrum Sensing Based on Random Transition of the Primary User in Laplacian Noise

  • Conference paper
  • First Online:
Cognitive Radio Oriented Wireless Networks and Wireless Internet (CROWNCOM 2021, WiCON 2021)

Abstract

In this paper, cooperative spectrum sensing (CSS) of dynamic primary user (PU) is considered in Laplacian noise environment. The dynamic PU is characterized by its transitions from ON (present) state to OFF (absent) state and vice-versa. It means, during the entire sensing duration, the PU appears or disappears intermittently. We assume that each cognitive radio (CR) uses conventional test-statistics such as energy detection (ED), absolute value cumulation detection (AVCD) and improved AVCD (i-AVCD). The hard decision from each CR fuses at the fusion center (FC) according to CSS based on OR rule (CSS-OR), CSS-AND rule and CSS-majority rule to make a final decision on the appearance or disappearance of the PU. We further consider dynamic nature of the PU in terms of its arrival rate \((\theta _{A})\) and departure rate \((\theta _{D})\). We present performance of the CSS of dynamic PU using receiver operating characteristic (ROC) and detection probability (\(P_D\)) versus average signal-to-noise ratio (SNR), denoted by \(\gamma \), using Monte Carlo simulations. We conclude that the CSS-OR rule based spectrum sensing outperforms CSS-majority rule and CSS-AND rule based spectrum sensing over a wide range of average SNR, i.e., \(-10<\gamma <10\) dB. We further conclude that CSS-AND rule is unsuitable for enhancing the detection probability of conventional sensing schemes. Furthermore, CSS-majority rule outperforms conventional sensing schemes ED, AVCD and i-AVCD beyond \(\gamma =-1,~-5\) and \(-6\) dB, respectively.

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

Access this chapter

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

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Li, F., Lam, K., Li, X., Sheng, Z., Hua, J., Wang, L.: Advances and emerging challenges in cognitive internet-of-things. IEEE Trans. Indus. Inform. 16(8), 5489–5496 (2020). https://doi.org/10.1109/TII.2019.2953246

    Article  Google Scholar 

  2. Lin, H., Hu, J., Ma, J., Xu, L., Yu, Z.: A secure collaborative spectrum sensing strategy in cyber-physical systems. IEEE Access 5, 27679–27690 (2017). https://doi.org/10.1109/ACCESS.2017.2767701

    Article  Google Scholar 

  3. Rappaport, T.S., et al.: Wireless communications and applications above 100 GHZ: opportunities and challenges for 6G and beyond. IEEE Access 7, 78729–78757 (2019). https://doi.org/10.1109/ACCESS.2019.2921522

    Article  Google Scholar 

  4. Karimzadeh, M., Rabiei, A.M., Olfat, A.: Soft-limited polarity-coincidence-array spectrum sensing in the presence of non-gaussian noise. IEEE Trans. Veh. Technol. 66(2), 1418–1427 (2017). https://doi.org/10.1109/TVT.2016.2570139

    Article  Google Scholar 

  5. Choi, K.W., Hossain, E.: Opportunistic access to spectrum holes between packet bursts: a learning-based approach. IEEE Trans. Wirel. Commun. 10(8), 2497–2509 (2011). https://doi.org/10.1109/TWC.2011.060711.100154

    Article  Google Scholar 

  6. Liang, Y., Chen, K., Li, G.Y., Mahonen, P.: Cognitive radio networking and communications: an overview. IEEE Trans. Veh. Technol. 60(7), 3386–3407 (2011). https://doi.org/10.1109/TVT.2011.2158673

    Article  Google Scholar 

  7. Wang, W., Zhang, H.: Slotted secondary transmission with adaptive modulation and coding under interweave cognitive radio. IEEE Trans. Veh. Technol. 68(5), 4800–4809 (2019). https://doi.org/10.1109/TVT.2019.2904285

    Article  Google Scholar 

  8. Ali, A., Hamouda, W.: Advances on spectrum sensing for cognitive radio networks: theory and applications. IEEE Commun. Surv. Tutor. 19(2), 1277–1304 (2017). https://doi.org/10.1109/COMST.2016.2631080

    Article  Google Scholar 

  9. Liang, Y., Zeng, Y., Peh, E.C.Y., Hoang, A.T.: Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wirel. Commun. 7(4), 1326–1337 (2008). https://doi.org/10.1109/TWC.2008.060869

    Article  Google Scholar 

  10. Tang, L., Chen, Y., Hines, E.L., Alouini, M.: Performance analysis of spectrum sensing with multiple status changes in primary user. Traffic 16(6), 874–877 (2012). https://doi.org/10.1109/LCOMM.2012.041112.120507

    Article  Google Scholar 

  11. Zandi, M., Dong, M., Grami, A.: Distributed stochastic learning and adaptation to primary traffic for dynamic spectrum access. IEEE Trans. Wirel. Commun. 15(3), 1675–1688 (2016). https://doi.org/10.1109/TWC.2015.2495154

    Article  Google Scholar 

  12. Liu, M., Zhao, N., Li, J., Leung, V.C.M.: Spectrum sensing based on maximum generalized correntropy under symmetric alpha stable noise. IEEE Trans. Veh. Technol. 68(10), 10262–10266 (2019). https://doi.org/10.1109/TVT.2019.2931949

    Article  Google Scholar 

  13. Zou, Y., Yao, Y., Zheng, B.: Outage probability analysis of cognitive transmissions: Impact of spectrum sensing overhead. IEEE Trans. Wirel. Commun. 9(8), 2676–2688 (2010). https://doi.org/10.1109/TWC.2010.061710.100108

    Article  Google Scholar 

  14. Pradhan, H., Kalamkar, S.S., Banerjee, A.: Sensing-throughput tradeoff in cognitive radio with random arrivals and departures of multiple primary users. IEEE Commun. Lett. 19(3), 415–418 (2015). https://doi.org/10.1109/LCOMM.2015.2393305

    Article  Google Scholar 

  15. Beaulieu, N.C., Chen, Y.: Improved energy detectors for cognitive radios with randomly arriving or departing primary users. IEEE Signal Process. Lett. 17(10), 867–870 (2010). https://doi.org/10.1109/LSP.2010.2064768

    Article  Google Scholar 

  16. Chang, K., Senadji, B.: Spectrum sensing optimisation for dynamic primary user signal. IEEE Trans. Commun. 60(12), 3632–3640 (2012). https://doi.org/10.1109/TCOMM.2012.091712.110856

    Article  Google Scholar 

  17. Unnikrishnan, J., Veeravalli, V.V.: Algorithms for dynamic spectrum access with learning for cognitive radio. IEEE Trans. Signal Process. 58(2), 750–760 (2010). https://doi.org/10.1109/TSP.2009.202

    Article  MathSciNet  MATH  Google Scholar 

  18. MacDonald, S., Popescu, D.C., Popescu, O.: Analyzing the performance of spectrum sensing in cognitive radio systems with dynamic PU activity. IEEE Commun. Lett. 21(9), 2037–2040 (2017). https://doi.org/10.1109/LCOMM.2017.2705126

    Article  Google Scholar 

  19. Yilmaz, Y., Guo, Z., Wang, X.: Sequential joint spectrum sensing and channel estimation for dynamic spectrum access. IEEE J. Sel. Areas Commun. 32(11), 2000–2012 (2014). https://doi.org/10.1109/JSAC.2014.141105

    Article  Google Scholar 

  20. Win, M.Z., Scholtz, R.A.: Ultra-wide bandwidth time-hopping spread-spectrum impulse radio for wireless multiple-access communications. IEEE Trans. Commun. 48(4), 679–689 (2000). https://doi.org/10.1109/26.843135

    Article  Google Scholar 

  21. Hu, B., Beaulieu, N. C.: On characterizing multiple access interference in TH-UWB systems with impulsive noise models. In: 2008 IEEE Radio and Wireless Symposium, pp. 879–882, January 2008. https://doi.org/10.1109/RWS.2008.4463633

  22. Tan, F., Song, X., Leung, C., Cheng, J.: Collaborative spectrum sensing in a cognitive radio system with laplacian noise. IEEE Commun. Lett. 16(10), 1691–1694 (2012). https://doi.org/10.1109/LCOMM.2012.080312.120517

    Article  Google Scholar 

  23. Xiaomei Z., Champagne, B., Wei-Ping Z.: Cooperative spectrum sensing based on the RAO test in non-Gaussian noise environments. In: 2013 International Conference on Wireless Communications and Signal Processing, pp. 1–6 (2013). https://doi.org/10.1109/WCSP.2013.6677074

  24. Wu, J., Wang, C., Yu, Y., Song, T., Hu, J.: Performance optimisation of cooperative spectrum sensing in mobile cognitive radio networks. IET Commun. 14, 1028–1036 (2020). https://doi.org/10.1049/iet-com.2019.1083

    Article  Google Scholar 

  25. Düzenli, T., Akay, O.: A new spectrum sensing strategy for dynamic primary users in cognitive radio. IEEE Commun. Lett. 20(4), 752–755 (2016). https://doi.org/10.1109/LCOMM.2016.2527640

    Article  Google Scholar 

  26. Ye, Y., Li, Y., Lu, G., Zhou, F., Zhang, H.: Performance of spectrum sensing based on absolute value cumulation in Laplacian noise. In: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 1–5 September 2017. https://doi.org/10.1109/VTCFall.2017.8287978

  27. Ye, Y., Li, Y., Lu, G., Zhou, F.: Improved energy detection with Laplacian noise in cognitive radio. IEEE Syst. J. 13(1), 18–29 (2019). https://doi.org/10.1109/JSYST.2017.2759222

    Article  Google Scholar 

  28. Sinha, K., Trivedi, Y.N.: Spectrum sensing based on dynamic primary user with additive Laplacian noise in cognitive radio. In: Caso, G., De Nardis, L., Gavrilovska, L. (eds.) CrownCom 2020. LNICSSITE, vol. 374, pp. 16–28. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-73423-7_2

    Chapter  Google Scholar 

  29. Geddes, K.O., Glasser, M.L., Moore, R.A., et al.: Evaluation of classes of definite integrals involving elementary functions via differentiation of special functions. Alegbra Eng. Commun. Comput. 1(2), 149–165 (1990)

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Khushboo Sinha .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sinha, K., Trivedi, Y.N. (2022). Performance of Cooperative Spectrum Sensing Based on Random Transition of the Primary User in Laplacian Noise. In: Jin, H., Liu, C., Pathan, AS.K., Fadlullah, Z.M., Choudhury, S. (eds) Cognitive Radio Oriented Wireless Networks and Wireless Internet. CROWNCOM WiCON 2021 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-98002-3_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-98002-3_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98001-6

  • Online ISBN: 978-3-030-98002-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics