基于扰动特征分解和前馈调制的网络波动跳变信号抑制算法

Suppression Algorithm of Network Fluctuation Hop Signal Based on Perturbation Characteristic Decomposition and Feedforward Modulation

在网络切换和数据通信中,会产生一种网络波动下的时频跳变谐振信号,需要对这种网络波动跳变信号进行抑制,以提高网络稳定性。提出一种基于扰动特征分解和前馈调制的网络波动跳变信号抑制算法,构建网络波动跳变信号谐振数学模型,采用射线模型对网络跳变单频脉冲中的波动信号进行传播损失估计,基于多普勒频移算法提取扰动特征,利用混响慢变包络切片把波动跳变信号的能量聚集在扰动方向,在希尔伯特空间上对网络波动跳变信号进行扰动特征分解。设计前馈调制滤波器,实现对网络波跳变信号的前馈调制抑制。仿真结果表明,该算法能有效抑制网络波动跳变中的谐振信号,避免了信息损失,数据传输丢包率得到降低,实时性好,解决了大规模混合组网中启动滞后、服务器负载、颤抖等问题。

In the network switching and data communication,a network time-frequency hop resonant signal can be produced,and such fluctuation hop signal should be suppressed to improve network stability.An improved suppression algorithm of network fluctuation hop signal was proposed based on perturbation characteristic decomposition and feedforward modulation,and the network fluctuation hop signal resonant mathematical model was constructed.The ray model was used to estimate the transmission loss,Doppler frequency shift algorithm was used to extract disturbance characteristics,and slowly varying envelope slice was used to gather the signal energy in the disturbance direction.In the Hilbert space,perturbation characteristic decomposition was obtained,the feedforward filter was designed,and the signal suppression was completed.The simulation results show that this algorithm can effectively suppress the resonant signal in network fluctuation hop,the information loss is avoided,data packet loss rate is reduced,and it has good real-time performance.The problems such as network startup delay,server load,trembling are solved.