Digital Signal Processing

R. Ali ¹, O. Zahran ¹, M. El-Kordy ¹, F. E. Abd El-Samie ¹

Affiliations
1 Department of Electronics and Electrical Communication, Menoufia University, Menouf, EG

Abstract

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. 

Keywords

BSS, MIMO, PCA, ICA, MUK, MSK, GMSK, QPSK, MSE.

Full Text

     

R. Ali ¹, O. Zahran ², M. Elkordy ³, F. E. Abd El-Samie ²

Affiliations
1 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG
3 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG

Abstract

This paper studied the problem of blind signal separation (BSS) for the system of multiple input and multiple output signals (MIMO) of noisy signals. It uses 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.  We used the proposed algorithm with multi user kurtosis (MUK) that used for blind of mixed signals. 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 signal to noise ratio (SNR) between extracted and original signals to compare between them to give the better result. The separation of signals in a noisy environment is studied with and without the using the new technique. The simulation results confirm the usefulness of this technique.

Keywords

BSS, MIMO, MUK, SNR.

Full Text