Blind Source Separation for Different Modulation Techniques with Wavelet Denoising
This paper addresses the problem of blind signal separation (BSS) for the system of multiple input and multiple output signals (MIMO). We use different modulation techniques such as quadrature phase shift keying (QPSK), minimum shift keying (MSK), and Gaussian minimum shift keying (GMSK). Several methods have been used to solve this problem such as principle component analysis (PCA), independent component analysis (ICA), and multi user kurtosis (MUK) algorithms. We use different modulation techniques and different algorithms in the separation to compare between results and take into consideration the good separation. In this paper, we propose wavelet denoising with PCA, ICA and MUK methods. We consider the instantaneous mixture of two sources. The simulation results show a considerable improvement in extracted signals when compared to original signals. We assume mean square error (MSE) between extracted and original signals to compare between them to give the better result.
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