Skip to main content

Optimization of Collaborative Spectrum Sensing with Limited Time Resource

  • Conference paper
  • First Online:
Cognitive Radio Oriented Wireless Networks (CrownCom 2015)

Abstract

In this paper, Cognitive Radios (CRs) collaborate in spectrum sensing to detect random signals corrupted by Gaussian noise. Our analysis is based on a limited time resource assumption. This implies that the time resource dedicated for cooperative spectrum sensing process is constrained and shared between spectrum sensing time and results reporting time, which depends on the number of sensing users. We use common weighted gain combining detector to detect presence or absence of Primary User (PU). In order to find optimum gains, number of users and detection threshold, we maximize the achievable throughput with two approaches so that the predefined constraints on detection and false alarm probabilities are satisfied to protect the cooperative network performance quality. Analytical results in addition to simulation results show that the proposed schemes significantly outperform similar traditional detectors.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ahsant, B., Viswanathan, R.: A review of cooperative spectrum sensing in cognitive radios. In: Mukhopadhyay, S.C., Jayasundera, K.P., Fuchs, A. (eds.) Advancement in Sensing Technology. SSMI, vol. 1, pp. 69–80. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  2. Sedighi, S., Pourgharehkhan, Z., Taherpour, A., Khattab, T.: Distributed spectrum sensing of correlated observations in cognitive radio networks. In: 7th IEEE GCC Conference and Exhibition (GCC), IEEE 2013, pp. 483–488 (2013)

    Google Scholar 

  3. Pourgharehkhan, Z., Sedighi, S., Taherpour, A. Uysal, M.: Spectrum sensing of correlated subbands with colored noise in cognitive radios. In: Wireless Communications and Networking Conference (WCNC). IEEE, pp. 1017–1022 (2012)

    Google Scholar 

  4. Akyildiz, I.F., Lo, B.F., Balakrishnan, R.: Cooperative spectrum sensing in cognitive radio networks: a survey. Physical Communication 4(1), 40–62 (2011)

    Article  Google Scholar 

  5. Chen, Y.: Optimum number of secondary users in collaborative spectrum sensing considering resources usage efficiency. IEEE Communications Letters 12(12), 877–879 (2008)

    Article  Google Scholar 

  6. Althunibat, S., Granelli, F.: An objection-based collaborative spectrum sensing for cognitive radio networks. IEEE Communications Letters 18(8), 1291–1294 (2014)

    Article  Google Scholar 

  7. Li, H., Cheng, X., Li, K., Hu, C., Zhang, N., Xue, W.: Robust collaborative spectrum sensing schemes for cognitive radio networks. IEEE Transactions on Parallel andDistributed Systems 25(8), 2190–2200 (2014)

    Article  Google Scholar 

  8. Quan, Z., Cui, S., Sayed, A.H.: Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE Journal of Selected Topics in SignalProcessing 2(1), 28–40 (2008)

    Article  Google Scholar 

  9. Quan, Z., Cui, S., Sayed, A.: An optimal strategy for cooperative spectrum sensing in cognitive radio networks. In: Global Telecommunications Conference, GLOBECOM 2007. IEEE, pp. 2947–2951 (2007)

    Google Scholar 

  10. Peh, E., Liang, Y., Guan, Y., Zeng, Y.: Cooperative spectrum sensing in cognitive radio networks with weighted decision fusion schemes. IEEE Transactions on Wireless Communications 9(12), 3838–3847 (2010)

    Article  Google Scholar 

  11. Quan, Z., Cui, S., Sayed, A.H., Poor, H.V.: Optimal multiband joint detection for spectrum sensing in cognitive radio networks. IEEE Transactions on SignalProcessing 57(3), 1128–1140 (2009)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

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

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Fariba Mohammadyan or Tamer Khattab .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Mohammadyan, F., Pourgharehkhan, Z., Taherpour, A., Khattab, T. (2015). Optimization of Collaborative Spectrum Sensing with Limited Time Resource. In: Weichold, M., Hamdi, M., Shakir, M., Abdallah, M., Karagiannidis, G., Ismail, M. (eds) Cognitive Radio Oriented Wireless Networks. CrownCom 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 156. Springer, Cham. https://doi.org/10.1007/978-3-319-24540-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24540-9_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24539-3

  • Online ISBN: 978-3-319-24540-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics