The Journal of Korean Institute of Electromagnetic Engineering and Science (한국전자파학회논문지)

The Korean Institute of Electromagnetic Engineering and Science (한국전자파학회)
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A Cooperative K-out-of-n Spectrum Sensing Method Considering Optimal Threshold

최적의 임계값을 고려한 K-out-of-n 협력 스펙트럼 검출 기법

  • Choi, Moon-Geun (Department of Electronic Engineering, University of Ulsan) ;
  • Kong, Hyung-Yun (Department of Electronic Engineering, University of Ulsan)
  • 최문근 (울산대학교 전기전자정보시스템부) ;
  • 공형윤 (울산대학교 전기전자정보시스템부)
  • Published : 2011.08.31
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Abstract

In this paper, to improve performance of spectrum sensing, we propose the method which can find optimal threshold based on power of PU(Primary User) signal. To find optimal threshold value, we will use mathematical method, and find threshold which can has lowest error probability. Each SU(Secondary User) use this threshold and All Su makes local decision. All Su Send local decision to FC(Fusion Center). In this paper we consider K-out-of-n rule to combining local decision. To make global decision value, FC find optimal n. In the FC. FC received local decision which has lowest error probability and using optimal n and these vaule. FC make global decision value. In this paper, to analysis performance proposed scheme, we simulate proposed scheme using matlab and compare with traditional OR Rule. As a result of simulation, we can know that preposed scheme can get a better performance than traditional OR rule.

본 논문에서는 에너지 검출 기법의 성능을 향상시키기 위해 각각의 SU(Secondary User)에서 수신한 PU(Primaty User) 신호의 크기를 바탕으로 대수적 연산을 통해 에러 확률이 가장 낮은 최적의 임계값을 찾아 PU의 신호를 검출하는 기법을 제안하며 최적의 임계값을 고려해 생성된 local decision을 바탕으로 가장 낮은 에러 확률을 보이는 K-out-of-n 법칙에 적용하는 방법을 연구한다. 각각의 SU에서 최적의 임계값을 찾고 본 논문에서 제안하는 기법의 성능 평가를 위해 Matlab을 이용하여 이를 시뮬레이션하고, 기존의 협력 스펙트럼 검출 기법 중 하나인 OR 법칙과 비교 분석한다. Matlab을 이용한 시뮬레이션 결과, 최적의 임계값을 이용한 K-out-of-n 법칙이 기존의 OR 법칙에 비해 오 경보 확률 및 미 검출 확률이 감소한 것을 알 수 있다.

Keywords

References

  1. Mark A. McHenry, "NSF spectrum occupancy measurements project summary", no. FY2004-013, Aug. 2005.
  2. Simon Haykin, "Cognitive radio: Brain-empowered wireless communications", IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, Feb. 2005. https://doi.org/10.1109/JSAC.2004.839380
  3. Tevfik Yu¨cek, Hu¨seyin Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications", IEEE Communications Surveys & Tutorials, vol. 11, no. 1, pp. 116-130, First Quarter 2009. https://doi.org/10.1109/SURV.2009.090109
  4. Amir Ghasemi, Elvino S. Sousa, "Opportunistic spectrum access in fading channels through collaborative sensing", Journal of Communications, vol. 2, no. 2, pp. 71-82, Mar. 2007.
  5. Fadel F. Digham, Mohamed-Slim Alouini, and Marvin K. Simon, "On the energy detection of unknown signals over fading channels", IEEE Inter. Conf. Communications(ICC), pp. 3575-3579, Anchorage Alaska, USA, May 2003. https://doi.org/10.1109/ICC.2003.1204119
  6. Moon Geun Choi, Hyung Yun Kong, "A study of the or rule to reduce decision time of primary user at the cognitive radio", IWIT Journal, vol. 10, no. 5, pp. 161-166, Oct. 2010.
  7. Amir Ghasemi, Elvino S. Sousa, "Collaborative spectrum sensing for opportunistic access in fading environments", IEEE DySPAN 2005, pp. 131-136, Baltimore, MD, USA, Dec. 2005. https://doi.org/10.1109/DYSPAN.2005.1542627
  8. Wei Zhang, Ranjan K. Mallik, and Khaled Ben Letaief, "Cooperative spectrum sensing optimization in cognitive radio networks", Communications, 2008. ICC '08. IEEE International Conference on, pp. 3411-3415, Beijing, China, May 2008. https://doi.org/10.1109/ICC.2008.641
  9. Wei Zhang, Ranjan K. Mallik, and Khaled Ben Letaief, "Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks", Wireless Communications, IEEE Transactions on, vol. 8, Issue 12, pp. 5761-5766, Dec. 2009. https://doi.org/10.1109/TWC.2009.12.081710