Convolutive Blind Source Separation for Communication Signals Based on the Sliding Z-Transform

Abstract

Convolutive blind source separation (CBSS) is one of the main branches in the field of intelligent signal processing. Inspired by the thought of sliding discrete Fourier transform (DFT), an idea of the sliding Z-transform is introduced in the present study. Based on the sliding Z-transform, a method called the sliding Z-transform for CBSS (ZCBSS) is applied to CBSS for communication signals with the same or different frequency. It is found that the deduced algorithm can accomplish the separation task without setting any preset parameter and directly recover time-domain sources from the convolutive mixtures with the help of robust instantaneous blind source separation algorithms. Simulations are carried out accordingly, and it is concluded that the proposed approach is effective in terms of both separation performance and signal de-noising.

Keywords

• Blind source separation
• convolutive mixture
• sliding Z-transform
• signal de-noising