利用频谱峰值特征的窄带频谱感知方法

沈连腾 1; 2; 巩克现 1; 潘一苇 1; 范磊 1

doi:10.7652/xjtuxb201606011

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利用频谱峰值特征的窄带频谱感知方法

更新时间：2025-07-09

- 利用频谱峰值特征的窄带频谱感知方法
- Spectrum Sensing Method of Narrow-Bands Based on Peak Feature of Spectrums
- 西安交通大学学报 2016年50卷第6期页码：68-74
- 作者机构：
  
  1. 解放军信息工程大学信息系统工程学院,郑州,450001
  2. 解放军95898部队, 157300, 黑龙江绥芬河
- 作者简介：
- 基金信息：
  
  : 2015-11-14。作者简介: 沈连腾(1986—),男,硕士生;巩克现(通信作者),男,副教授,硕士生导师。基金项目: 国家自然科学基金资助项目(61072046,61401511)
- DOI：10.7652/xjtuxb201606011
  中图分类号： TN92
- 网络首发：2016-06-10，
  
  纸质出版：2016
- 稿件说明：
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沈连腾 1, 2, 巩克现 1, 等. 利用频谱峰值特征的窄带频谱感知方法[J]. 西安交通大学学报, 2016,50(6):68-74.

Spectrum Sensing Method of Narrow-Bands Based on Peak Feature of Spectrums[J]. 2016, 50(6): 68-74.
沈连腾 1, 2, 巩克现 1, 等. 利用频谱峰值特征的窄带频谱感知方法[J]. 西安交通大学学报, 2016,50(6):68-74. DOI： 10.7652/xjtuxb201606011.

Spectrum Sensing Method of Narrow-Bands Based on Peak Feature of Spectrums[J]. 2016, 50(6): 68-74. DOI： 10.7652/xjtuxb201606011.

摘要

针对全盲条件下窄带频谱感知在低信噪比时性能不理想的问题

提出了一种基于频谱峰值局部密度的频谱感知(MTSE-MLD)方法。该方法对接收信号采用多窗谱(MTSE)估计功率谱

提取其最大值组成峰值序列

借鉴聚类思想利用频谱峰值局部密度的最大值(MLD)作为检测统计量

理论推导并仿真验证了其服从Ⅱ型极值分布

从而得到给定虚警概率下的检测门限

实现信号的盲检测。实验结果表明:MTSE-MLD方法无需任何先验信息

对噪声方差不敏感

适用于加性高斯白噪声信道与多径衰落信道下通信信号的检测; 在数据量相同的条件下

与特征值能量法相比性能提高了1 dB。

Abstract

A spectrum sensing method based on local density of spectrum peaks(MTSE-MLD method)is proposed to address the problem that the spectrum sensing of narrow-bands under the blind condition is not ideal in low SNR performance. Power spectrums of received signals are estimated by the multitaper spectral estimation(MTSE)

and their maximum spectrum peak values are obtained to form a sequence of spectrum peaks. It follows from the idea of clustering that the maximum local density(MLD)of the spectrum peak is used as the detection statistic. Theoretical derivation and simulations verify that the statistic obeys an extreme value distribution of type II. A detection threshold with a given false alarm probability is obtained

and the blind detection of signals is realized. The MTSE-MLD method does not need any priori information

and is not sensitive to any noise variance. Experimental results show that the method is suitable for the detection of various common signals under the condition of additive Gauss white noise channel and multi-path fading channel. A comparison with the method based on eigenvalue energy under the same amount of data shows that the detection performance of the proposed method improves by 1 dB.

关键词

Keywords

references

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