吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (4): 1297-1303.doi: 10.13229/j.cnki.jdxbgxb201504039

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基于随机共振和MIMO技术的协方差矩阵频谱感知算法

赵晓晖, 李晓燕   

  1. 吉林大学 通信工程学院,长春 130012
  • 收稿日期:2013-06-17 出版日期:2015-07-01 发布日期:2015-07-01
  • 作者简介:赵晓晖(1957-),男,教授,博士生导师.研究方向:信号处理理论在通信中的应用.E-mail:xhzhao@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目 (61171079)

Covariance matrix spectrum sensing algorithm based on stochastic resonance and MIMO technology

ZHAO Xiao-hui, LI Xiao-yan   

  1. College of Communication Engineering, Jilin University, Changchun 130012,China
  • Received:2013-06-17 Online:2015-07-01 Published:2015-07-01

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摘要： 在认知无线电系统中,为了使认知用户可以在低信噪比和衰落信道的条件下实现可靠的频谱感知,提出了基于随机共振和MIMO的协方差矩阵频谱感知算法。该算法将随机共振和MIMO技术用于协方差矩阵频谱感知,同时还给出了判决门限的计算方法。仿真实验结果表明:与不使用随机共振和MIMO技术的频谱感知算法相比,本文算法具有更高的检测性能;并且当天线数足够多时,该算法可以在很低信噪比情况下实现可靠的频谱感知。

关键词: 通信技术, 频谱感知, 随机共振, MIMO技术, 协方差矩阵

Abstract: In order to achieve reliable spectrum sensing by users under the condition of low Signal-to-Noise Ratio (SNR) and fading channel in cognitive radio systems, a new covariance matrix spectrum sensing algorithm based on stochastic resonance and Multi-input-Multi-output (MIMO) technology is proposed; and the calculation method of the decision threshold is derived. Simulations show that the performance of the proposed algorithm is batter than the algorithm without introduction of the stochastic resonance and MIMO technology. When the number of antennae is large enough, the proposed method can achieve good performance at low SNR.

Key words: communications, spectrum sensing, stochastic resonance, MIMO technology, covariance matrix

中图分类号: 

  • TN929
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