Skip to main content
SpringerLink
Log in

An improved cyclostationary feature detection based on the selection of optimal parameter in cognitive radios

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

Spectrum sensing is an important part of cognitive radio systems to find spectrum hole for transmission which enables cognitive radio systems coexist with the authorized radio systems without harmful interference. In this paper, an improved cyclostationary feature detection method is proposed to reduce computational complexity without loss of good performance based on the optimal parameter selection strategy for choosing detection parameters of cyclic frequency and lag. Taking binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals as examples, the theoretical analyses are presented for choosing the optimal parameters. Simulation results are given to certify the correctness of the proposed parameter selection strategy and show the performance of the proposed method.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Haykin S. Cognitive radio: Brain-empowered wireless communications [J]. IEEE Journal on Selected Areas in Communications, 2005, 23(2): 201–220.

    Article  Google Scholar 

  2. Akyildiz I F, Lee WY, Vuran M C, et al. Next generation dynamic spectrum access cognitive radio wireless networks: A survey [J]. Computer Networks, 2006, 50(13): 2127–2159.

    Article  MATH  Google Scholar 

  3. Cabric D, Mishra S M, Brodersen R W. Implementation issues in spectrum sensing for cognitive radios [C]// Proceedings of the 38th Asiomar Conference on Signals, Systems and Computers. Monterey, Canada: IEEE, 2004: 772–776.

    Google Scholar 

  4. Urkowitz H. Energy detection of unknown deterministic signals [J]. Proceedings of the IEEE, 1967, 55(4): 523–531.

    Article  Google Scholar 

  5. Tandra R, Sahai A. SNR walls for signal detection [J]. IEEE Journal on Selected Topics in Signal Processing, 2008, 2(1): 4–17.

    Article  Google Scholar 

  6. Wiliam A G. Exploitation of spectral redundancy in cyclostationary signals [J]. IEEE Signal Processing Magazine, 1991, 8(2): 14–36.

    Article  Google Scholar 

  7. Dandawate A V, Giannakis G B. Statistical tests for presence of cyclostationarity [J]. IEEE Transactions on Signal Processing, 1994, 42(9): 2355–2369.

    Article  Google Scholar 

  8. Sutton P D, Nolan K E, Doyle L E. Cyclostationary signatures in practical cognitive radio applications [J]. IEEE Journal on Selected Areas in Communications, 2008, 26(1): 13–24.

    Article  Google Scholar 

  9. Choi K W, Jeon W S, Jeong D G. Sequential detection of cyclostationary signal for cognitive radio systems [J]. IEEE Transactions on Wireless Communications, 2009, 8(9): 4480–4485.

    Article  Google Scholar 

  10. Lunden J, Koivunen V, Huttunen A, et al. Collaborative cyclostationary spectrum sensing for cognitive radio systems [J]. IEEE Transactions on Signal Processing, 2009, 57(11): 4182–4195.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai, 200240, China

    Da Shen  (沈 达), Di He  (何 迪) & Ying-pei Lin  (林英沛)

  2. ARCON Corporation, Waltham, 02451, USA

    Wen-hua Li  (李文化)

Authors
  1. Da Shen  (沈 达)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Di He  (何 迪)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wen-hua Li  (李文化)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ying-pei Lin  (林英沛)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Da Shen  (沈 达).

Additional information

Foundation item: the National Natural Science Foundation of China (Nos. 60802058 and 60832009) and the SMC Young Teacher Sponsorship of Shanghai Jiaotong University

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shen, D., He, D., Li, Wh. et al. An improved cyclostationary feature detection based on the selection of optimal parameter in cognitive radios. J. Shanghai Jiaotong Univ. (Sci.) 17, 1–7 (2012). https://doi.org/10.1007/s12204-012-1222-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-012-1222-z

Key words

CLC number

Search

Navigation