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基于空間譜的頻譜感知算法及性能分析

黨小宇 李阿明 虞湘賓

黨小宇, 李阿明, 虞湘賓. 基于空間譜的頻譜感知算法及性能分析[J]. 電子與信息學(xué)報(bào), 2016, 38(5): 1179-1185. doi: 10.11999/JEIT150823
引用本文: 黨小宇, 李阿明, 虞湘賓. 基于空間譜的頻譜感知算法及性能分析[J]. 電子與信息學(xué)報(bào), 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

基于空間譜的頻譜感知算法及性能分析

doi: 10.11999/JEIT150823
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61172078, 61201208),教育部留學(xué)回國(guó)人員科研啟動(dòng)基金和中央高校基本科研業(yè)務(wù)費(fèi)(NS2014038),南京航空航天大學(xué)研究生創(chuàng)新基地開(kāi)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: 現(xiàn)有的基于特征值或譜密度的頻譜感知算法,多分別使用近似高斯分布和Tracy-Widom分布來(lái)分別分析求解檢驗(yàn)統(tǒng)計(jì)量在信號(hào)是否存在時(shí)的分布,未能給出統(tǒng)一的解析表達(dá)式。該文提出均勻線陣(ULA)條件下基于空間譜密度比的頻譜感知算法,并且基于順序統(tǒng)計(jì)量的最新研究成果,給出檢驗(yàn)統(tǒng)計(jì)量統(tǒng)一的閉合表達(dá)式。該算法基于離散空間譜密度最大最小值的比建立檢驗(yàn)統(tǒng)計(jì)量。仿真結(jié)果表明,對(duì)于8陣元的ULA,在采樣點(diǎn)數(shù)為1000、檢測(cè)概率為0.9時(shí),所提算法比最大最小特征值(MME)比算法有約1.7 dB的性能優(yōu)勢(shì),同時(shí)也有效驗(yàn)證了檢驗(yàn)統(tǒng)計(jì)量理論分布的準(zhǔn)確性。
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出版歷程
  • 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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