Skip to main content
Log in

Detection time analysis for the multiple-user cooperative spectrum sensing scheme in cognitive radio networks

  • Published:
Science in China Series F: Information Sciences Aims and scope Submit manuscript

Abstract

In this paper, a novel multiple-user cooperative spectrum sensing (MCSS) scheme is proposed to achieve the spatial diversity gains for cognitive radio (CR) networks, where only the best relay, selected among all the candidate relays in accordance with the quality of channel conditions, is utilized to cooperatively detect the primary user. Closed-form expressions of detection time for the traditional non-cooperative and the proposed MCSS schemes are derived over Rayleigh fading channels. In addition, numerical experimentations are conducted to make a performance comparison between the non-cooperative sensing and our scheme. The result shows that by exploiting the multiple-user cooperation, the detection time is reduced greatly and moreover, diversity gains obtained by the MCSS scheme increase with a rise in the number of candidate relays.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Haykin S. Cognitive radio: brain-empowered wireless communications. IEEE JSAC, 2005, 23(2): 201–220

    Google Scholar 

  2. Ghozzi M, Dohler M, Marx F, et al. Cognitive radio: Methods for the detection of free band. CR Phys Elsevier, 2006, 7: 794–804

    Google Scholar 

  3. Akyildiz I F, Lee W Y, Vuran M C, et al. Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Comput Netw, 2006, 50: 2127–2159

    Article  MATH  Google Scholar 

  4. Sahai A, Hoven N, Tandra R. Some fundamental limits in cognitive radio. In: Proc Allerton Conf on Commun Control and Computing, Monticello, IL, USA, 2004

  5. Ghasemi A, Sousa E S. Collaborative spectrum sensing for opportunistic access in fading environment. In: Proc IEEE DYSPAN, Baltimore, Maryland, USA, 2005

  6. Cabric D, Mishra S M, Brodersen R W. Implementation issues in spectrum sensing for cognitive radios. In: Proc 38th Asilomar Conf on Signals, Systems and Computers, Pacific Grove, USA, 2004

  7. Kostylev V I. Energy detection of a signal with random amplitude. In: Proc IEEE Int Conf Commun, New York, NY, 2002

  8. Digham F F, Alouini M -S, Simon M K. On the energy detection of unknown signals over fading channels. In: Proc IEEE Int Conf Commun, Anchorage, AK, USA, 2003

  9. Fehske A, Gaeddert J D, Reed J H. A new approach to signal classification using spectral correlation and neural networks. In: Proc IEEE DYSPAN, Baltimore, Maryland, USA, 2005

  10. Mishra S M, Sahai A, Broderson R W. Cooperative sensing among the cognitive radio. In: Proc IEEE, ICC, Istanbul, Turkey, 2006

  11. Varshney P K, Burrus C S. Distributed Detection and Data Fusion. New York: Springer, 1997

    Google Scholar 

  12. Poor H V. An Introduction to Signal Detection and Estimation. Berlin: Springer-Verlag, 1994

    MATH  Google Scholar 

  13. Zhi Q, Cui S, Sayed A H. Optimal linear cooperation for spectrum sensing in cognitive radio networks. IEEE JST Signal Proc, 2008, 2(1): 28–40

    Google Scholar 

  14. Peng Q, Zeng K, Wang J, et al. A distributed spectrum sensing scheme based on credibility and evidence theory in cognitive radio context. In: Conf Helsinki PIMRC, 2006

  15. Ganesan G, Li Y G. Cooperative spectrum sensing in cognitive radio-part I: Two user networks. IEEE Trans Wirel Commun, 2007, 6(6): 2204–2213

    Article  Google Scholar 

  16. Ganesan G, Li Y G. Cooperative spectrum sensing in cognitive radio—part II: Multiuser networks. IEEE Trans Wirel Commun, 2007, 6(6): 2214–2222

    Article  Google Scholar 

  17. Zhu J, Zheng B, Zou Y. Spectrum sensing through user cooperation in cognitive radio networks over Rayleigh fading channels. submitted to Chin J Electr.

  18. Zou Y, Zheng B, Zhu J. Outage analysis of opportunistic cooperation over Rayleigh fading channels. IEEE Trans Wirel Commun, 2009, 8(6): 3077–3085

    Article  Google Scholar 

  19. Varshney P K, Burrus C S. Distributed Detection and Data Fusion. New York: Springer, 1997

    Google Scholar 

  20. Hillenbrand J, Weiss T, Jondral F K. Calculation of detection and false alarm probabilities in spectrum pooling systems. IEEE Commun Lett, 2005, 9: 349–351

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jia Zhu.

Additional information

Supported by the Postgraduate Innovation Program of Scientific Research of Jiangsu Province (Grant Nos. CX08B 080Z, CX09B 150Z), the National Natural Science Foundation of China (Grant No. 60972039), the Key Project of Natural Science Funding of Jiangsu Province (Grant No. BK2007729), the National High-Tech Research & Development Program of China (Grant No. 2009AA01Z241), and the Major Development Program of Jiangsu Educational Committee (Grant No. 06KJA51001)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhu, J., Zheng, B. & Zou, Y. Detection time analysis for the multiple-user cooperative spectrum sensing scheme in cognitive radio networks. Sci. China Ser. F-Inf. Sci. 52, 1915–1925 (2009). https://doi.org/10.1007/s11432-009-0166-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-009-0166-x

Keywords

Navigation