Comparative performance evaluation of error regularized Turbo-MIMO MMSE-SIC detectors in Gaussian channels

We evaluate the performance of a set of low complexity successive interference cancellation (SIC) detection algorithms in comparison to optimal maximum a-posteriori probability (MAP) detection and low complexity linear filter detection in a Turbo multiple-input multiple-output (Turbo-MIMO) system. We show that both linear and SIC soft detection algorithms perform similarly poorly for iterative receivers, even if the channel decoder output is available at the detector. We propose a low complexity combined a-priori/a-posteriori information-based error regularization technique, that improves the performance of the Turbo-MIMO design considerably. With this regularization technique, we show that a decoding gain of 2.2 dB can be achieved in an LTE compliant Turbo-MIMO receiver.