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基于高阶统计特征的空时分组码盲识别方法

闫文君 张立民 凌青 洪丹枫

闫文君, 张立民, 凌青, 洪丹枫. 基于高阶统计特征的空时分组码盲识别方法[J]. 电子与信息学报, 2016, 38(3): 668-673. doi: 10.11999/JEIT150739
引用本文: 闫文君, 张立民, 凌青, 洪丹枫. 基于高阶统计特征的空时分组码盲识别方法[J]. 电子与信息学报, 2016, 38(3): 668-673. doi: 10.11999/JEIT150739
YAN Wenjun, ZHANG Limin, LING Qing, HONG Danfeng. An Algorithm for Blind Classification of Space-time Block Code Based on Higher-order Statistics[J]. Journal of Electronics & Information Technology, 2016, 38(3): 668-673. doi: 10.11999/JEIT150739
Citation: YAN Wenjun, ZHANG Limin, LING Qing, HONG Danfeng. An Algorithm for Blind Classification of Space-time Block Code Based on Higher-order Statistics[J]. Journal of Electronics & Information Technology, 2016, 38(3): 668-673. doi: 10.11999/JEIT150739

基于高阶统计特征的空时分组码盲识别方法

doi: 10.11999/JEIT150739
基金项目: 

国家自然科学基金(61102167)

An Algorithm for Blind Classification of Space-time Block Code Based on Higher-order Statistics

Funds: 

The National Natural Science Foundation of China (61102167), Taishan Scholar Special Foundation

  • 摘要: 空时分组码的盲识别是认知无线电领域一个新的重要问题。多数现有算法在多接收天线下进行识别,然而这些算法并不完全适用于单接收天线条件。针对上述问题,该文提出一种同时适用于单接收天线和多接收天线的空时分组码盲识别方法。利用空时分组码矩阵内元素的相关性,提出四阶统计量作为盲识别的特征参数,并通过最小欧氏距离的方式检验四阶统计量的差异,达到识别的目的。蒙特卡洛仿真表明,算法识别性能较好,且不需要预先知道信道信息、噪声信息和调制信息,对多普勒频移和相位噪声具有一定的适应性。
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出版历程
  • 收稿日期:  2015-06-18
  • 修回日期:  2015-10-15
  • 刊出日期:  2016-03-19

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