基于随机共振的双门限协作频谱感知算法

刘顺兰; 肖义德; 包建荣

doi:10.11959/j.issn.1000-0801.2020248

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基于随机共振的双门限协作频谱感知算法

研究与开发 | 更新时间：2024-06-05

- 基于随机共振的双门限协作频谱感知算法
- Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance
- 电信科学 2020年36卷第12期页码：33-40
- 作者机构：
- 作者简介：
  
  [ "刘顺兰（1965- ），女，杭州电子科技大学电子信息学院教授，主要研究方向为信息与信号处理、无线通信等" ]
  [ "肖义德（1995- ），男，杭州电子科技大学电子信息学院硕士生，主要研究方向为信号处理、无线通信等" ]
  [ "包建荣（1978- ），男，博士，杭州电子科技大学电子信息学院教授，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：
- DOI：10.11959/j.issn.1000-0801.2020248
  中图分类号： TN925
- 网络出版日期：2020-12，
  
  纸质出版日期：2020-12-20
- 稿件说明：
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刘顺兰, 肖义德, 包建荣. 基于随机共振的双门限协作频谱感知算法[J]. 电信科学, 2020,36(12):33-40.

Shunlan LIU, Yide XIAO, Jianrong BAO. Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance[J]. Telecommunications science, 2020, 36(12): 33-40.
刘顺兰, 肖义德, 包建荣. 基于随机共振的双门限协作频谱感知算法[J]. 电信科学, 2020,36(12):33-40. DOI： 10.11959/j.issn.1000-0801.2020248.

Shunlan LIU, Yide XIAO, Jianrong BAO. Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance[J]. Telecommunications science, 2020, 36(12): 33-40. DOI： 10.11959/j.issn.1000-0801.2020248.

摘要

针对现有频谱感知算法在低信噪比（SNR）环境中性能检测不佳的问题以及传统随机共振（SR）检测弱信号的方法在实际应用中存在的局限性，通过设置最优门限，计算出最优的协作用户数量，提出了一种基于随机共振的双门限协作频谱感知算法，并对提出的算法进行了性能分析。DCSSR算法通过将位于双门限不确定区域的统计数据经过随机共振系统，进一步提高频谱感知算法在低信噪比下的检测性能。仿真结果表明，在不同信噪比和虚警概率下，DCSSR算法相较于传统单门限能量协作算法、双门限能量协作算法以及单门限随机共振协作算法，检测性能都得到了提升。在信噪比为-20 dB时，提出的DCSSR算法相较于传统单门限能量检测协作算法，检测概率提高了80%。

Abstract

In view of the poor performance of the existing spectrum sensing algorithm in the low signal-noise ratio (SNR) environment and the limitations of traditional stochastic resonance (SR) detection methods for weak signals in practical applications

a dual threshold cooperative spectrum sensing algorithm based on stochastic resonance (DCSSR) by setting the optimal threshold was proposed and the optimal number of cooperative users was calculated.At last

the performance of the proposed algorithm was analyzed.This algorithm further improves the detection performance of the spectrum sensing algorithm under low signal-to-noise ratio by passing the statistical data located in the double-threshold uncertain region through a stochastic resonance system.Simulation results show that the detection performance of DCSSR algorithm is improved compared with traditional single threshold energy cooperation algorithm

double threshold energy cooperation algorithm and single threshold stochastic resonance cooperation algorithm.When the SNR is -20 dB

the proposed DCSSR algorithm improves the detection probability by 80% compared with the traditional single threshold energy detection cooperation algorithm.

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references

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