高检测概率协方差矩阵机会协作频谱感知

刘顺兰; 王静; 包建荣

doi:10.11959/j.issn.1000−0801.2019001

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高检测概率协方差矩阵机会协作频谱感知

研究与开发 | 更新时间：2024-06-05

- 高检测概率协方差矩阵机会协作频谱感知
- Covariance matrix opportunistic cooperative spectrum sensing of high detection probability
- 电信科学 2019年35卷第1期页码：67-73
- 作者机构：
- 作者简介：
  
  [ "刘顺兰（1965− ），女，杭州电子科技大学教授，主要研究方向为信息与信号处理、无线通信等。" ]
  [ "王静（1994− ），女，杭州电子科技大学硕士生，主要研究方向为信号处理、无线通信等。" ]
  [ "包建荣（1978− ），男，博士，杭州电子科技大学教授，主要研究方向为空间无线通信、通信信号处理与自主无线电等。" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;The Zhejiang Provincial Natural Science Foundation of China(No.LY18F010013);浙江省自然科学基金资助项目;The Zhejiang Provincial Natural Science Foundation of China(No.LY17F010019);国家自然科学基金资助项目;The National Natural Science Foundation of China(No.61471152)
- DOI：10.11959/j.issn.1000−0801.2019001
  中图分类号： TN925
- 网络出版日期：2019-01，
  
  纸质出版日期：2019-01-20
- 稿件说明：
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刘顺兰, 王静, 包建荣. 高检测概率协方差矩阵机会协作频谱感知[J]. 电信科学, 2019,35(1):67-73.

Shunlan LIU, Jing WANG, Jianrong BAO. Covariance matrix opportunistic cooperative spectrum sensing of high detection probability[J]. Telecommunications science, 2019, 35(1): 67-73.
刘顺兰, 王静, 包建荣. 高检测概率协方差矩阵机会协作频谱感知[J]. 电信科学, 2019,35(1):67-73. DOI： 10.11959/j.issn.1000−0801.2019001.

Shunlan LIU, Jing WANG, Jianrong BAO. Covariance matrix opportunistic cooperative spectrum sensing of high detection probability[J]. Telecommunications science, 2019, 35(1): 67-73. DOI： 10.11959/j.issn.1000−0801.2019001.

摘要

针对现有频谱感知算法检测概率较低导致的感知性能较差的问题，提出了协方差矩阵机会协作（covariance matrix opportunity cooperation

CMOC）频谱感知算法。该算法在传统协方差矩阵感知基础上，通过奇偶时隙划分实现机会协作，且根据错误虚警概率和门限间的关系，推导出检测概率的解析解，可较精确地实现频谱感知检测。仿真结果验证了所提算法可明显提高频谱感知的检测概率。在瑞利衰落信道的信噪比为−10 dB时，相对于现有无中继协作的能量检测频谱感知算法和无中继协作的协方差频谱感知算法，检测概率分别提高0.19和0.13。而且，该算法还具有较高能效且复杂度适中，非常适合新一代无线通信频谱认知应用。

Abstract

According to the problem of poor sensing performance caused by the existing spectrum sensing algorithm

the covariance matrix opportunistic cooperative (CMOC) spectrum sensing algorithm was proposed. Based on the traditional covariance matrix spectrum sensing algorithm

odd and even slots were divided by the new proposed algorithm

then opportunistic cooperation was added. The relationship between the false alarm probability and the threshold of the new algorithm was also analyzed

and the analytic detection probability was deduced for the actualization of the more accurate spectrum sensing detection. The simulation results verify that the proposed algorithm obviously improves the detection probability. In Rayleigh fading channel

the detection probability is increased by 0.19 and 0.13

which compared with the existing energy detection spectrum sensing algorithm without relay cooperative and the covariance matrix spectrum sensing algorithm without relay cooperation

when the SNR is −10 dB. Moreover

the proposed algorithm has high energy efficiency as well as the moderate computational complexity

so it is especially suited for the spectrum cognition applications in the new generation wireless communication.

关键词

Keywords

references

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