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基于随机矩阵理论的协作频谱感知

王磊 郑宝玉 李雷

王磊, 郑宝玉, 李雷. 基于随机矩阵理论的协作频谱感知[J]. 电子与信息学报, 2009, 31(8): 1925-1929. doi: 10.3724/SP.J.1146.2008.01154
引用本文: 王磊, 郑宝玉, 李雷. 基于随机矩阵理论的协作频谱感知[J]. 电子与信息学报, 2009, 31(8): 1925-1929. doi: 10.3724/SP.J.1146.2008.01154
Wang Lei, Zheng Bao-yu, Li Lei. Cooperative Spectrum Sensing Based on Random Matrix Theory[J]. Journal of Electronics & Information Technology, 2009, 31(8): 1925-1929. doi: 10.3724/SP.J.1146.2008.01154
Citation: Wang Lei, Zheng Bao-yu, Li Lei. Cooperative Spectrum Sensing Based on Random Matrix Theory[J]. Journal of Electronics & Information Technology, 2009, 31(8): 1925-1929. doi: 10.3724/SP.J.1146.2008.01154

基于随机矩阵理论的协作频谱感知

doi: 10.3724/SP.J.1146.2008.01154
基金项目: 

国家自然科学基金(60372107,10471114),江苏省自然科学基金基础研究计划(BK2007729),江苏省高校自然科学重大基础研究项目(06KJA51001)和江苏省高校自然科学基金(04KJB110097)资助课题

Cooperative Spectrum Sensing Based on Random Matrix Theory

  • 摘要: 认知无线电频谱共享技术在新一代无线通信网络中具有广泛的应用前景,频谱感知是其中最重要的环节。该文提出了一种新的在多认知用户环境中,基于大维随机矩阵理论的协作频谱感知算法。充分利用随机矩阵的渐近谱分布特性及小样本下最大特征值收敛特性来提高感知性能。理论分析和仿真结果均表明,新算法性能明显优于同类算法和典型的能量检测算法。
  • Sahai A. Spectrum sensing: Fundamental limits and practicalchallenges, DySPAN 2005 tutorial part I [C]. DySPAN 2005,Maryland, Nov 2005: 1-138.[2]Cardoso L S, Debbah M, and Bianchi P. Cooperativespectrum sensing using random matrix theory [C]. ISWPC,Santorini, 7-9 May 2008: 334-338.[3]Zeng Yong-hong and Liang Ying-chang. Maximum minimumeigenvalue detection for cognitive radio [C]. The 18th AnnualIEEE International Symposium on Personal, Indoor andMobile Radio Communications (PIMRC'07), Athens, 3-7Sept. 2007: 1-5.[4]Tulino A M and Verdu S. Random Matrix Theory andWireless Communications [M]. Boston: Now Publishers Inc,2004: 168-189.[5]Mehta M L. Random Matrices [M]. Third edition, London:Academic Press, 2006: 394-438.[6]Bai Z D and Silverstein Jack W. Spectral Analysis of LargeDimensional Random Matrices [M]. Beijing: Science Press,2006: 283-357.[7]Bai Z D. Methodologies in spectral analysis of largedimensional random matrices, a review [J]. Statistica Sinica,1999, 9(1): 611-677.[8]Johnstone I M. On the distribution of the largest eigenvaluein principle components analysis [J]. The Annals of Statistics,2001, 29(2): 295-327.[9]Johansson K. Shape fluctuations and random matrices [J].Communications in Mathematical Physics.2000, 209(2):437-476[10]Tracy C A and Widom H. On orthogonal and symplecticmatrix ensembles [J]. Communications in MathematicalPhysics, 1996, 177(3): 727-754.[11]Ghasemi A and Sousa E S. Collaborative spectrum sensingfor opportunistic access in fading environments [C]. FirstIEEE International Symposium on New Frontiers in DynamicSpectrum Access Networks (DySPAN 2005), Maryland, Nov2005: 131-136.[12]Ghasemi A and Sousa E S. Spectrum Sensing in CognitiveRadio Networks: The Cooperation-Processing Tradeoff [M].USA: WILEY, 2007: 1049-1060.
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出版历程
  • 收稿日期:  2008-09-16
  • 修回日期:  2009-03-04
  • 刊出日期:  2009-08-19

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