基于室内可见光通信的EMD-ICA联合降噪方案

EMD-ICA Combined Noise Reduction Scheme Based on Indoor Visible Light Communication

背景噪声是消除可见光通信的重要组成部分。为此,本文提出一种基于经验模态分集(EMD)和独立分量分析(ICA)的联合去噪算法,能较好地实现有效信号与背景噪声的分离。该算法结合EMD自适应将信号分解为不同尺度振动模式的优点和ICA提取独立源信号的优点,对含噪信号进行EMD分解,获得固有模态分量(IMF),并采用模态相关准则对信号层与噪声层进行判定,将分界上的IMF分量构建虚拟噪声通道,基于ICA算法对原始信号进行信噪分离,从而得到降噪后的信号。

Background noise is an important part of eliminating visible light communication. To this end, this article proposes a joint denoising algorithm based on empirical mode diversity(EMD) and independent component analysis(ICA), which can better separate the effective signal from the background noise. The algorithm combines the advantages of EMD adaptive decomposition of the signal into different scale vibration modes and the advantage of ICA to extract independent source signals. The noisy signal is EMD decomposed to obtain the intrinsic modal component(IMF), and the modal correlation criterion is used to analyze the signal The layer and the noise layer are determined, the IMF component on the boundary is constructed as a virtual noise channel, and the original signal is separated from the original signal based on the ICA algorithm, so as to obtain the reduced signal.