Precoded MIMO Multiuser Scheme for Diversity Fairness

Tomlinson-Harashima precoding, design the transmit signal so that the ISI in the receiver side is very minimum. In this precoding moving the feedback filter to the transmit side to avoid error propagation problem. In this paper depth analysis of zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to multi-input multi-output (MIMO) systems. We investigate the bit error rate performance of two types of equalizers namely ZF and MMSE for BPSK system. Zero Forcing Equalizer, applies the inverse of the channel to the received signal, to restore the signal before the channel. So this will be very useful when ISI is significant compared to noise. A minimum mean square error (MMSE) describes the approach which minimizes the mean square error (MSE), which is a common measure of estimator quality. MMSE equalizer, it does not usually eliminate ISI completely but, minimizes the total power of the noise and ISI components in the output.