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Volume 33 Issue 2
Mar.  2011
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Chunjiang BAI, Wanzhao CUI, Jun LI. Prediction of Passive Intermodulation Level Based on Chaos Method[J]. Journal of Electronics & Information Technology, 2021, 43(1): 124-130. doi: 10.11999/JEIT190977
Citation: Zhao Chun-Hui, Ma Shuang, Yang Wei-Chao. Spectrum Sensing in Cognitive Radios Based on Fractal Box Dimension[J]. Journal of Electronics & Information Technology, 2011, 33(2): 475-478. doi: 10.3724/SP.J.1146.2010.00314

Spectrum Sensing in Cognitive Radios Based on Fractal Box Dimension

doi: 10.3724/SP.J.1146.2010.00314
  • Received Date: 2010-03-29
  • Rev Recd Date: 2010-07-23
  • Publish Date: 2011-02-19
  • To reduce the computational complexity of spectrum sensing and improve the spectrum sensing performance, a spectrum sensing method based on the fractal box dimension was proposed. As the box dimensions of noise and signal are different, the fractal box dimension is used as test statistics. The simulation results demonstrate the proposed method has good detection performance under Gaussian white noise, and it is not sensitive to the noise. Furthermore, this method is low computational complexity and easy to implement.
  • Sridhara 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[2]Haykin S. Cognitive radio: brain-empowered wireless communications [J].IEEE Journal Selected Areas in Commun.2005, 23(2):201-220[3]Chen 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.[4]Cabric 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.[5]Jarmo 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.[6]Renzo 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.[7]Lunden 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[8]崔丽, 王金龙, 吴启晖等. 认知无线电中基于信息简约的最大似然协同频谱感知算法[J].电子与信息学报.2009, 31(9):2177-2182浏览Cui Li, Wang Jin-long, and Wu Qi-hui, et al.. Maximum likelihood cooperative spectrum sensing algorithm based on contracted information in cognitive radio systems[J].Journal of Electronics Information Technology.2009, 31(9):2177-2182[9]Hu 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.[10]吕铁军, 郭双兵, 肖先赐. 调制信号的分形特征研究[J]. 中国科学E辑, 2001, 31(6): 508-513.Lv Tie-jun, Guo Shuang-bing, and Xiao Xian-ci. Research of fractal features of the modulated signal [J]. Science in China, Ser.E, 2001, 31(6): 508-513.[11]Danijela 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.
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