基于能量和小波变换的双门限联合频谱感知

doi:10.13190/j.jbupt.2017.04.019

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (4): 117-121.doi: 10.13190/j.jbupt.2017.04.019

基于能量和小波变换的双门限联合频谱感知

倪水平^1,2, 常慧刚²

1. 北京邮电大学电子工程学院, 北京 100876;
2. 河南理工大学计算机科学与技术学院, 河南焦作 454000

收稿日期:2017-01-05 出版日期:2017-08-28 发布日期:2017-07-10
作者简介:倪水平(1977-),男,副教授,E-mail:nishuiping@hpu.edu.cn.
基金资助:
国家自然科学基金项目（60872149）；河南省科技攻关项目（172102210023）

Double-Threshold Joint Spectrum Sensing Based on Energy and Wavelet Transform

NI Shui-ping^1,2, CHANG Hui-gang²

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. School of Computer Science and Technology, Henan Polytechnic University, Henan Jiaozuo 454000, China

Received:2017-01-05 Online:2017-08-28 Published:2017-07-10

摘要/Abstract

摘要： 传统的能量感知算法对噪声比较敏感，在较低的信噪比条件下检测准确性易受到影响，循环特征检测法计算复杂度偏高，为此提出了基于能量检测和小波变换（WT）感知的双门限联合检测算法.该算法对双门限区间以外的区域采用能量检测进行判定，双门限范围内的不确定区域进行小波感知，并根据信道中噪声不确定性自适应调整双门限值，当信道质量较好时，减小两门限之间的距离，否则增大两门限之间的距离，从而控制进行小波感知的概率.仿真结果表明，此算法有效地提高了低信噪比条件下系统的检测性能，降低了算法的复杂度.

关键词: 联合检测, 小波变换, 双门限, 能量检测

Abstract: Considering that the traditional energy detection algorithm is sensitive to noise, the detection accuracy is easy to be affected in low signal-to-noise ratio (SNR) conditions, and that cyclostationary detection algorithm is high computing complexity, a double-threshold joint detection algorithm based on energy detection and wavelet transform (WT) sensing was proposed. When the decision statistic falls outside the double-threshold section, the energy detection is performed and the confused region is within the double-threshold for wavelet detection. Besides, the two thresholds can be adjusted adaptively according to noise uncertainty. When the channel quality is better, the distance of the two thresholds will be minished, otherwise the distance of the two thresholds will be larger, so as to control the probability of wavelet detection. Simulation shows that the proposed algorithm can improve the detection performance effectively under low SNR conditions, and reduces the complexity.

Key words: joint detection, wavelet transform, double-threshold, energy detection

中图分类号:

TN929.53

倪水平, 常慧刚. 基于能量和小波变换的双门限联合频谱感知[J]. 北京邮电大学学报, 2017, 40(4): 117-121.

NI Shui-ping, CHANG Hui-gang. Double-Threshold Joint Spectrum Sensing Based on Energy and Wavelet Transform[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(4): 117-121.

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基于能量和小波变换的双门限联合频谱感知

Double-Threshold Joint Spectrum Sensing Based on Energy and Wavelet Transform

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