The Journal of the Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회논문지)

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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A Cooperative Spectrum Sensing Method based on Eigenvalue and Superposition for Cognitive Radio Networks

인지무선네트워크를 위한 고유값 및 중첩기반의 협력 스펙트럼 센싱 기법

  • Miah, Md. Sipon (School of Electrical Engineering, University of Ulsan) ;
  • Koo, Insoo (School of Electrical Engineering, University of Ulsan)
  • Received : 2013.07.20
  • Accepted : 2013.08.16
  • Published : 2013.08.31
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Abstract

Cooperative spectrum sensing can improve sensing reliability, compared with single node spectrum sensing. In addition, Eigenvalue-based spectrum sensing has also drawn a great attention due to its performance improvement over the energy detection method in which the more smoothing factor, the better performance is achieved. However, the more smoothing factor in Eignevalue-based spectrum sensing requires the more sensing time. Furthermore, more reporting time in cooperative sensing will be required as the number of nodes increases. Subsequently, we in this paper propose an Eigenvalue and superposition-based spectrum sensing where the reporting time is utilized so as to increase the number of smoothing factors for autocorrelation calculation. Simulation result demonstrates that the proposed scheme has better detection probability in both local as well as global detection while requiring less sensing time as compared with conventional Eigenvalue-based detection scheme.

단일 노드 스펙트럼 센싱과 비교했을 때, 협력스펙트럼 센싱은 스펙트럼 센싱의 신뢰도를 크게 향상 시킬 수 있다. 또한 고유값(Eigenvalue)기반의 스펙트럼 센싱 기법은 에너지 검출 기반의 센싱 기법에 비해 센싱 성능을 제공할 수 있기 때문에 최근 많은 관심을 끌고 있다. 고유값(Eigenvalue)기반의 스펙트럼 센싱 기법의 성능은 smoothing factor (SF)가 증가함에 따라 더 좋은 센싱 결과를 얻을 수 있으나, SF값이 증가함에 따라 더 긴 센싱 시간이 요구된다. 더나가 협력 스펙트럼의 경우, 노드수가 증가함에 따라 더 많은 전송시간이 요구됨으로, 고유값(Eigenvalue)기반의 협력 스펙트럼 센싱의 경우 SF값이 센싱 시간을 결정하는 중요한 요소가 된다. 이에 본 논문에서는 센싱 시간을 증가하지 않고 SF값을 증가시킬 수 있는 고유값 및 중첩기반의 협력 스펙트럼 센싱 기법을 제안한다. 제안된 방식에서는 SF값을 증가시키기 위하여 전송(reporting) 시간을 활용한다. 시뮬레이션을 통해 제안된 방식이 기존 고유값 (Eigenvalue)기반의 센싱기법에 비교하여 더 작은 센싱 시간을 유지하면서 국부(local) 센싱값 및 전체(global) 센싱값을 향상 시킬 수 있음을 보였다.

Keywords

References

  1. J. Mitola and G. Q. Maguire, "Cognitive radios: making software radios more personal," IEEE Personal Communications, vol. 6, no. 4, pp. 13-18, 1999. https://doi.org/10.1109/98.788210
  2. S. Haykin, "Cognitive radio: brain-empowered wireless communications," IEEE Transaction on Communications, vol. 23, no. 2, pp. 201-220, 2005.
  3. D. Cabric, S. Mishra, and R. Brodersen, "Implementation issues in spectrum sensing for cognitive radios," Proceedings Signals, Systems and Computers, 2004. Conference Record of the 38th Asilomar Conference, vol. 1, pp. 772-776, 2004.
  4. N. Nguyen-Thanh and I. Koo, "An enhanced cooperative spectrum sensing scheme based on evidence theory and reliability source evaluation in cognitive radio context," IEEE Communications Letters, vol. 13, no. 7, pp. 492 -494, 2009. https://doi.org/10.1109/LCOMM.2009.090043
  5. G. Ganesan and Y. G. Li, "Cooperative spectrum sensing in cognitive radio-part I: two user networks," IEEE Transaction Wireless Communication, vol. 6, pp. 2204-2213, 2007. https://doi.org/10.1109/TWC.2007.05775
  6. Z. Wei, R.K. Mallik, and K. Ben Letaief, "Cooperative spectrum sensing optimization in cognitive radio networks," Proceedings of IEEE International Conference on Communications, pp. 3411-3415, 2008.
  7. L. Chen, J. Wang, and S. Li, "An adaptive cooperative spectrum sensing scheme based on the optimal data fusion rule," Proceedings of 4th International Symposium on Wireless Communication Systems, pp. 582-586, 2007.
  8. Sahai and D. Cabric, "Spectrum sensing: fundamental limits and practical challenges," Proceedings of IEEE International Symposium New Frontiers Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, 2005.
  9. Y. Zeng, Y. Liang, "Eigenvalue-based Spectrum Sensing Algorithms for Cognitive Radio," IEEE Transaction on Communications, vol. 57, no.6, 2009.
  10. Xi Yang, Kejun Lei, Shengliang Peng, and Xiuying Cao, "Blind detection for primary user based on the sample covariance matrix in cognitive radio," IEEE Communications Letters, vol. 15, no. 1, 2011.
  11. T. Ratnarajah, C. Zhong, A. Kortun, M. Sellathurai and C. B. Papadias, "Complex random matrices and multiple antenna spectrum sensing," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3848-3851, 2011.
  12. Jing Jin, Hongbo Xu, Hua Li, Chunjian Ren, "Superposition-Based Cooperative Spectrum Sensing in Cognitive Radio Networks," 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).
  13. Zhai Xuping, Pan Jianguo, "Energy-detection based spectrum sensing for cognitive radio," IET Conference on Wireless, Mobile and Sensor Networks 2007(CCWMSN07), Shanghai, China, pp.12-14, 2007.
  14. Saman Atapattu, C. Tellambura, and H. Jiang, "Energy detection based cooperative spectrum sensing in cognitive radio networks," IEEE Transaction on Wireless Communications, vol. 10, no. 4, 2011.
  15. N. Tung and I. Koo, "Fuzzy-based Dynamic Packet Scheduling Algorithm for Multimedia Cognitive Radios," The Journal of The Institute of Internet, Broadcasting and Communication, Vol.12, No.3, pp.1-7, 2012. http://dx.doi.org/10.7236/JIWIT.2012.12.3.1
  16. W. Choi, and S. Lee, "Pilot Signal Estimation- Based ATSC Signal Sensing Using a Wiener Filter," Journal of Korean Institute of Information Technology, vol. 11, issue 6, pp. 39-45, June 2013.