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基于次用户功率控制辅助的合作频谱感知

申滨 王志强 青晗

申滨, 王志强, 青晗. 基于次用户功率控制辅助的合作频谱感知[J]. 电子与信息学报, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232
引用本文: 申滨, 王志强, 青晗. 基于次用户功率控制辅助的合作频谱感知[J]. 电子与信息学报, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232
Bin SHEN, Zhiqiang WANG, Han QING. Secondary User Power Control Aided Cooperative Spectrum Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232
Citation: Bin SHEN, Zhiqiang WANG, Han QING. Secondary User Power Control Aided Cooperative Spectrum Sensing[J]. Journal of Electronics & Information Technology, 2018, 40(10): 2337-2344. doi: 10.11999/JEIT171232

基于次用户功率控制辅助的合作频谱感知

doi: 10.11999/JEIT171232
基金项目: 重庆市自然科学基金项目(cstc2016jcyjA0595)
详细信息
    作者简介:

    申滨:男,1978年生,教授,研究方向为认知无线电、IR-UWB等

    王志强:男,1991年生,硕士生,研究方向为认知无线电

    青晗:男,1994年生,硕士生,研究方向为认知无线电

    通讯作者:

    申滨  shenbin@cqupt.edu.cn

  • 中图分类号: TN92

Secondary User Power Control Aided Cooperative Spectrum Sensing

Funds: The Municipal Natural Science Foundation of Chongqing (cstc2016jcyjA0595)
  • 摘要: 传统的合作频谱感知一般将感知环境建模为单级信道,且次用户一般都以相同的发射功率向数据融合中心报告感知数据,难以体现并利用不同次用户感知数据之间的空间分集差异。为解决此问题并有效地设置次用户在感知数据上报阶段的发射功率,该文提出了3种最优功率控制方案,以获得相应设计准则下参与合作感知的次用户最优发射功率。在融合中心理想具备感知信道和报告信道的统计特性时,通过理论推导获得了基于信道统计特性的功率控制闭式解方案;当信道统计特性难以现实具备时,分别获得了基于联合信道统计特性估计的最大特征功率矢量及盲加权多特征功率矢量方案。理论分析和仿真实验表明,在不同的先验信息条件下,3种方案的性能皆远优于缺少功率控制的合作感知方案。
  • 图  1  不同最优功率控制方案的检测性能

    图  2  盲加权多特征向量方案的检测性能

    图  3  盲加权最优功率控制方案的检测性能

    图  4  不同最优功率控制方案的检测性能

    图  5  不同功率控制方案的虚警概率

  • AXELL E, LEUS G, and LARSSON E G. Overview of spectrum sensing for cognitive radio[C]. IEEE International Workshop on Cognitive Information Processing, Elba, 2010: 322–327.
    CICHOŃ K, KLIKS A, and BOGUCKA H. Energy-efficient cooperative spectrum sensing: A survey[J]. IEEE Communications Surveys&Tutorials, 2016, 18(3): 1861–1886 doi: 10.1109/COMST.2016.2553178
    MA Jun and LI Ye. Soft combination and detection for cooperative spectrum sensing in cognitive radio networks[C]. Global Communications Conference, 2007. GLOBECOM '07, Washington, DC, USA, 2007: 3139–3143.
    ZHOU Fuhui, LI Zan, SI Jingbo, et al. Adaptive secondary-user selection without prior information for cooperative spectrum sensing in CRNs[C]. IEEE International Conference on Computer, Information and Telecommunication Systems, Gijon, 2015: 1–5.
    ABDI N, YAZDIAN E, and HOSEINI A M D. Optimum number of secondary users in cooperative spectrum sensing methods based on random matrix theory[C]. International Conference on Computer and Knowledge Engineering, Mashhad 2015: 290–294.
    申滨, 喻俊, 黄琼, 等. 基于EEF准则的认知无线电宽带频谱感知[J]. 北京邮电大学学报, 2014, 37(6): 115–119 doi: 10.13190/j.jbupt.2014.06.024

    SHEN Bin, YU Jun, HUANG Qiong, et al. EEF criterion based wideband spectrum sensing used in cognitive radio[J]. Journal of Beijing University of Posts and Telecommunications, 2014, 37(6): 115–119 doi: 10.13190/j.jbupt.2014.06.024
    ZENG Yonghong and LIANG Yingchang. Eigenvalue-based spectrum sensing algorithms for cognitive radio[J]. IEEE Transactions on Communications, 2009, 57(6): 1784–1793 doi: 10.1109/TCOMM.2009.06.070402
    弥寅, 卢光跃. 基于特征值极限分布的合作频谱感知算法[J]. 通信学报, 2015, 36(1): 84–89 doi: 10.11959/j.issn.1000-436x.2015010

    MI Yin and LU Guangyue. Cooperative spectrum sensing algorithm based on limiting eigenvalue distribution[J]. Journal on Communications, 2015, 36(1): 84–89 doi: 10.11959/j.issn.1000-436x.2015010
    ZHANG Rui, LIM T J, LIANG Yingchang, et al. Multi-antenna based spectrum sensing for cognitive radios: A GLRT approach[J]. IEEE Transactions on Communications, 2010, 58(1): 84–88 doi: 10.1109/TCOMM.2010.01.080158
    ZENG Yonghong, LIANG Yingchang, and ZHANG Rui. Blindly combined energy detection for spectrum sensing in cognitive radio[J]. IEEE Signal Processing Letters, 2008, 15(1): 649–652 doi: 10.1109/LSP.2008.2002711
    曹开田, 杨震. 一种新型的基于最大特征值的合作频谱感知算法[J]. 电子与信息学报, 2011, 33(6): 1367–1372 doi: 10.3724/SP.J.1146.2010.01091

    CAO Kaitian and YANG Zhen. A novel cooperative spectrum sensing algorithm based on the maximum eigenvalue[J]. Journal of Electronics&Information Technology, 2011, 33(6): 1367–1372 doi: 10.3724/SP.J.1146.2010.01091
    MA Jun, ZHAO Guodong, and LI Ye. Soft combination and detection for cooperative spectrum sensing in cognitive radio networks[J]. IEEE Transactions on Wireless Communications, 2008, 7(11): 4502–4507 doi: 10.1109/T-WC.2008.070941
    SEDIGHI S, TAHERPOUR A, GAZOR S, et al. Eigenvalue-based multiple antenna spectrum sensing: higher order moments[J].IEEE Transactions on Wireless Communications, 2017, 16(2): 1168–1184 doi: 10.1109/TWC.2016.2640299
    ZHOU Fushui, BEAULIEU N C, LI Zan, et al. Feasibility of maximum eigenvalue cooperative spectrum sensing based on Cholesky factorisation[J]. Communications IET, 2016, 10(2): 199–206 doi: 10.1049/iet-com.2015.0252
    ZHANG Wensheng, SUN Jian, XIONG Hailiang, et al. A new joint eigenvalue distribution of finite random matrix for cognitive radio networks[J]. IET Communications, 2016, 10(13): 1584–1589 doi: 10.1049/iet-com.2015.0869
    LI Zan, ZHOU Fushui, SI Jingbo, et al. Feasibly efficient cooperative spectrum sensing scheme based on Cholesky decomposition of the correlation matrix[J]. IET Communications, 2016, 10(9): 1003–1011 doi: 10.1049/iet-com.2015.0654
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出版历程
  • 收稿日期:  2017-12-18
  • 修回日期:  2018-05-23
  • 网络出版日期:  2018-07-30
  • 刊出日期:  2018-10-01

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