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Abstract

This paper addresses the problem of blind signal separation (BSS) for the system of multiple input and multiple output signals (MIMO). Different modulation techniques such as quadrature phase shift keying (QPSK), minimum shift keying (MSK), and Gaussian minimum shift keying (GMSK) have been considered. Several methods have been investigated to solve this problem such as principle component analysis (PCA), independent component analysis (ICA), and multi user kurtosis (MUK) algorithms. Different modulation techniques and different algorithms in the separation have been investigated to for comparison between results. In this paper, we propose wavelet denoising with PCA, ICA and MUK methods. We use the separation algorithm for the discrete cosine transforms (DCT) for blind of mixed signals, instead of separating the mixtures themselves, as a technique that achieves a great result in eliminating the noise. The proposed algorithm is used with multi user kurtosis (MUK) that used for blind of mixed signals with considering the instantaneous mixture of two sources. The simulation results show a considerable improvement in extracted signals when compared to original signals