Robust blind multiuser detection in overdetermined MIMO channels using wavelet transform

Abstract

In the conventional multiple input multiple output (MIMO) systems, the receiver needs users to transmit their channel state information (CSI) to the receiver, but this approach increases bandwidth usage and affects spectral efficiency, and decreases effective data rate. Since the spectrum is a limited resource, blind source separation (BSS) approaches are efficient and promising options for the MIMO systems in a way that they do not require CSI to detect and separate the users’ data. On the other hand, one of the interesting techniques for denoising signals is to use discrete wavelet transform (DWT). The main objective of this paper is to present an application of DWT-BSS approach for the MIMO systems for the case where more receiver antennas than transmitter (users’) antennas are available. One of the simple approaches in BSS is to use the natural gradient algorithm (NG) which has linear convergence speed and has disappointing results in impulsive noise environments. We have used complex FastICA rather than the NG because of its cubic convergence speed and robustness to noise. Our simulations demonstrate that the proposed DWT-BSS scheme outperforms the NG method especially when channel noise becomes different from the additive white Gaussian noise (AWGN).