Adaptive decision feedback detection with parallel interference cancellation and constellation constraints for multiuser multi-input-multi-output systems

In this study, a novel low-complexity adaptive decision feedback (DF) detection with parallel DF (P-DF) and P-DF constellation constraints (P-DFCC) is proposed for multiuser multi-input-multi-output (MIMO) systems. The authors propose a constrained constellation map which introduces a number of selected points served as the feedback candidates for interference cancellation. By introducing a reliability checking, a higher degree of freedom is introduced to refine the unreliable estimates. The P-DFCC is followed by an adaptive receive filter to estimate the transmitted symbol. To reduce the complexity of computing the filters with time-varying MIMO channels, an adaptive recursive least squares algorithm is employed in the proposed P-DFCC scheme. An iterative detection and decoding (Turbo) scheme is considered with the proposed P-DFCC algorithm. Simulations show that the proposed technique has a complexity comparable to the conventional P-DF detector while it obtains a performance close to the maximum-likelihood detector at a low to medium signal-to-noise ratio range..