期刊文献+

基于分形相关盒维数的恒虚警检测方法

Constant False Alarm Detection Method Based on Related Box Dimension
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摘要 为了提高低信噪比下频谱感知的有效性和可靠性,提出了一种基于分形相关盒维数的恒虚警检测方法。通过对信号进行自相关运算一定程度上可消除噪声的影响;对于判决门限只是凭借经验进行设定,虚警概率无法进行量化计算,通过实验拟合可知,噪声相关盒维数大致服从高斯正态分布,利用恒虚警检测可得到判决门限。仿真结果表明,基于该假设的门限值在检测概率一定的条件下,所得到的虚警概率与设定值相同,提高了感知结果的可信性;相关运算消除噪声影响,提高了信号的感知率。 To improve the credibility and effectiveness of spectrum sensing under the low signal to noise rate, this paper presents a CFAR (constant false alarm) detection method based on fractional related box dimension. The influence of the noise can be weakened by the related operation of the signal. Because the threshold main- ly is set only by our experience, the probability of false-alarm could not be calculated. By the experiment fit- ting, we can know the box dimension of noise basically obeys the Gaussian distribution. The threshold by the constant false alarm detection can be gotten. Simulation results show that by the threshold based on the constant false alarm detection can a same probability of false-alarm as that we set be gotten. The related operation weakens the influence of the noise. This method improves the credibility of spectrum sensing and the possibili- ty of detection of the algorithm.
出处 《通信对抗》 2013年第4期1-4,共4页 Communication Countermeasures
关键词 频谱感知 相关盒维数 恒虚警 判决门限 spectrum sensing related box dimension constant false alarm(CFAR) threshold
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  • 1Sridhara K, Chandra A, and Tripathi P S M. Spectrum challenges and solutions by cognitive radio: an overview [J]. Wireless Personal Communications, 2008, 45(3): 281-291.
  • 2Haykin S. Cognitive radio: brain-empowered wireless communications [J]. IEEE Journal Selected Areas in Commun., 2005, 23(2): 201-220.
  • 3Chen Xiao-fei and Nagaraj S. Entropy based spectrum sensing in cognitive radio [C]. 7th Annual Wireless Telecommunications Symposium, Ponoma, CA, United States, April 2008: 57-61.
  • 4Cabrie D, Mishra S M, and Brodersen R W. Implementation issues in spectrum sensing for cognitive radios [C]. Proc. Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, United States, Nov. 2004, 1: 772-776.
  • 5Jarmo L, Visa K, Anu H, and Vincent P H. Spectrum sensing in cognitive radios based on multiple cyclic frequencies [C]. Proceedings of the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom, Orlando, FL, United States, August 2007: 37-43.
  • 6Renzo M D, Imbriglio L, and Graziosi F, et al. Cooperative spectrum sensing for cognitive radios: Performance analysis for realistic system setups and channel conditions [M]. Mobile Lightweight Wireless Systems, Berlin, Springer Berlin Heidelberg, 2009: 125-134.
  • 7Lunden J and Koivunen V, et al. Collaborative cyclostationary spectrum sensing for cognitive radio systems [J]. IEEE Transactions on Signal Processing, 2009, 57(11): 4182-4195.
  • 8Hu Z and Guo N, et al. Wideband waveform optimization with energy detector receiver in cognitive radio[C]. IEEE SoutheastCon 2010 Conference: Energizing Our Future, Charlotte-Concord, NC, United States, March 2010: 198-203.
  • 9Danijela C, Artem T, and Brodersen R W. Spectrum sensing measurements of pilot, energy, and collaborative detection[C]. Military Communications Conference 2006, Washington, D.C., United States, 2006: 1-7.
  • 10Lu Mingquan,电子科学学刊,1999年,16卷,3期,244页

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