Efficient Blind Signal Separation Algorithms for Wireless Multimedia Communication Systems

Abstract This paper studies the problem of multi-user blind signal separation (BSS) in wireless communications. The existing separation algorithms work on quadrature phase shift keying (QPSK). Through this work two proposed algorithms were presented to enhance the BSS performance. The first proposed algorithm uses wavelet denoising to remove noise from the received signals in time domain. It adopts different modulation techniques such as minimum shift keying (MSK), quadrature phase shift keying (QPSK), and Gaussian minimum shift keying (GMSK) then uses several BSS algorithms such as independent component analysis (ICA), principle component analysis (PCA), and multi user kurtosis (MUK) algorithms. The second proposed algorithm transfers the problem of BSS to transform domain and uses wavelet denoising to reduce noise effect on received mixture. BSS with Discrete Sine Transform (DST) and Discrete Cosine Transform (DCT) were investigated and compared to time domain performance. Minimum square error (MSE) and signal to noise ratio (SNR) were used as the evaluating metrics. Simulation results proved that in time domain, MUK with QPSK gives best performance and wavelet denoising was found to enhance the performance of BSS under all conditions. Signal separation in transform domain was found to give better performance than that in time domain due to the energy compaction process of these transforms and noise reduction due to their averaging effect.