干扰环境下通信传输信号优化仿真研究  

Simulation of Communication Transmission Signal Optimization under Interference Environment

作　　者：刘文霞[1] 

机构地区：[1]天津科技大学应用文理学院,天津300457

出　　处：《计算机仿真》2016年第5期192-195,共4页Computer Simulation

摘　　要：由于不同信号传输信道不同,导致信号传输过程中产生的大量噪声与信号形成较强的内在关联,造成信号精度差。传统的算法只是对传输信号进行简单的滤波处理,忽略了含噪信号存在的内在关联性而部分藏匿噪声不能消除的问题,导致去噪效果差。提出改进小波算法的干扰环境下的滤波通信方法。依据在干扰环境下通信序列的周期性组建干扰环境下的通信模型,将通信过程中的含噪信号分离问题转变为超定盲源分离问题,利用小波包分解原理,将通信的频带进行多频段划分,将没有划分的高频数据进行细致的分解,同时进行通信滤波消噪,采用软阈值和固定阈值来量化小波包系数,利用处理过的小波包系数对去噪后的信号进行重构,精确的实现了干扰环境下的滤波通信。仿真结果表明,改进小波算法在干扰环境下的滤波通信去噪效果好,鲁棒性强。A filtering communication method under interference environment based on improved wavelet algorithm is proposed.According to the periodicity of communication sequence under interference environment,a communication model under interference environment is established.The noised- signal separation problem in the process of communication is transformed into over-determined blind source separation problem.Using the wavelet packet decomposition principle,the frequency band of communication is made multi-band frequency division,and the highfrequency data which are not divided are made careful decomposition as well as communication filtering denoising.Soft threshold and fixed threshold are used to quantify wavelet packet coefficient,and by using the processed wavelet packet coefficient,the signal after denoising is reconstructed,and the filtering communication under interference environment is precisely realized.The simulation results show that the improved algorithm has good denoising effect and strong robustness.

关 键 词：盲源分离 单通道抗干扰 小波包变换 

分 类 号：TN911[电子电信—通信与信息系统]