Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance

Shunlan LIU; Yide XIAO; Jianrong BAO

doi:10.11959/j.issn.1000-0801.2020248

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Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance

Research and Development | 更新时间：2024-06-05

- Dual threshold cooperative spectrum sensing algorithm based on stochastic resonance
- Telecommunications Science Vol. 36, Issue 12, Pages: 33-40(2020)
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- DOI：10.11959/j.issn.1000-0801.2020248
  CLC： TN925
- Published Online：2020-12，
  
  Published：20 December 2020
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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：

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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