Impulsive noise mitigation in wireless communication systems using EMD technique

One physical process, which is not adequately described in terms of Gaussian models, is the process that generates “impulsive” interference bursts. These bursts occur in the form of short duration interferences, attaining large amplitudes. Many natural sources of interference exist, including lightning in the atmosphere or ice cracking in the arctic region. Among the manmade sources dominant source of impulsive interference occurs in the electricity supply industry. These noises can cause significant degradation of the performance of conventional wireless communication systems. This paper introduces a concept of impulsive noise reduction utilizing the Empirical Mode Decomposition (EMD) framework, where noisy signal is decomposed adaptively into oscillatory components called Intrinsic Mode Functions (IMFs) by means of a process called sifting. The EMD denoising involves filtering or thresholding each IMF and reconstructs the estimated signal using the processed IMFs. To simulate the denoising phenomenon, input information signals, impulsive noises and EMD algorithms were generated in Matlab. The input signals were degraded by adding impulsive noise and then empirical mode decomposition was performed on the noisy signals. Simulation results suggest that a signal corrupted by impulsive noise can be considerably recovered by the EMD method.