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基于空间谱的频谱感知算法及性能分析

党小宇 李阿明 虞湘宾

党小宇, 李阿明, 虞湘宾. 基于空间谱的频谱感知算法及性能分析[J]. 电子与信息学报, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823
引用本文: 党小宇, 李阿明, 虞湘宾. 基于空间谱的频谱感知算法及性能分析[J]. 电子与信息学报, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823
DANG Xiaoyu, LI Aming, YU Xiangbin. Spatial Spectrum Based Spectrum Sensing Algorithm and Performance Analysis[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823
Citation: DANG Xiaoyu, LI Aming, YU Xiangbin. Spatial Spectrum Based Spectrum Sensing Algorithm and Performance Analysis[J]. Journal of Electronics & Information Technology, 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823

基于空间谱的频谱感知算法及性能分析

doi: 10.11999/JEIT150823
基金项目: 

国家自然科学基金(61172078, 61201208),教育部留学回国人员科研启动基金和中央高校基本科研业务费(NS2014038),南京航空航天大学研究生创新基地开放基金(kfjj20150404)

Spatial Spectrum Based Spectrum Sensing Algorithm and Performance Analysis

Funds: 

The National Natural Science Foundation of China (61172078, 61201208), The State Education Ministry Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars and the Fundamental Research Funds for the Central Universities (NS2014038), The Foundation of Graduate Innovation Center in NUAA (kfjj20150404)

  • 摘要: 现有的基于特征值或谱密度的频谱感知算法,多分别使用近似高斯分布和Tracy-Widom分布来分别分析求解检验统计量在信号是否存在时的分布,未能给出统一的解析表达式。该文提出均匀线阵(ULA)条件下基于空间谱密度比的频谱感知算法,并且基于顺序统计量的最新研究成果,给出检验统计量统一的闭合表达式。该算法基于离散空间谱密度最大最小值的比建立检验统计量。仿真结果表明,对于8阵元的ULA,在采样点数为1000、检测概率为0.9时,所提算法比最大最小特征值(MME)比算法有约1.7 dB的性能优势,同时也有效验证了检验统计量理论分布的准确性。
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出版历程
  • 收稿日期:  2015-07-09
  • 修回日期:  2015-12-02
  • 刊出日期:  2016-05-19

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