基于子波变换的无线通信网络干扰信号检测研究

Research on interference signal detection based on wavelet transform in wireless communication network

在冗杂环境下,为有效识别无线通信网络干扰信号,提出基于子波变换的无线通信网络干扰信号检测研究。将干扰信号分为单音、多音、调频等类型,利用射线模型描述通信信道损失,确立噪声影响下的干扰信号结构,提取信号时频分布特征;在子波变换过程引入阈值滤波算法,将噪声投影在不同子波空间中,合理设置阈值,计算新的变换系数,实现信号去噪;采用混沌循环谱方法,将干扰信号检测转换为二元假设检验问题,获取二阶时变检测函数,计算决策量,结合门限值完成干扰信号检测。实验结果表明,该方法能够有效过滤噪声,检测出的干扰信号波形与频率与实际情况相符。

In order to effectively identify the interference signal of wireless communication network in the cluttered environment,the detection of interference signal of wireless communication network based on wavelet transform is proposed in this paper.The interference signal is divided into single tone,multi tone,frequency modulation and other types.The ray model is used to describe the loss of communication channel,establish the interference signal structure under the influence of noise,and extract the time-frequency distribution characteristics of signal.Threshold filtering algorithm is introduced in the wavelet transform process.Noise is projected into different wavelet spaces,the threshold is reasonably set and the new transformation coefficient is calculated to achieve signal denoising.The chaotic cyclic spectrum method is used to transform the interference signal detection into a binary hypothesis testing problem.The second-order time-varying detection function is obtained,and the decision quantity is calculated.Combined with the threshold value,the interference signal detection is completed.The experimental results show that the proposed method can effectively filter the noise,and the detected interference signal waveform and frequency are consistent with the actual situation.