Approximate maximum a posteriori detection for multiple-input-multiple-output systems with bit-level lattice reduction-aided detectors and successive interference cancellation

For iterative detection and decoding (IDD) in multiple-input–multiple-output (MIMO) systems, although the maximum a posteriori (MAP) detector can achieve an optimal performance, because of its prohibitively high computational complexity, various low-complexity approximate MAP detectors are studied. Among the existing MIMO detectors for the non-IDD receivers, lattice reduction (LR)-aided detectors can provide a near maximum-likelihood (ML) detector’s performance with reasonably low complexity, and they could be modified to be used in the IDD receivers. In this study, the authors propose a bit-level LR-aided MIMO detector whose performance can approach that of the MAP detector, where a priori information is taken into account for soft-decisions. Furthermore, the proposed method can be extended to large dimensional MIMO systems by channel matrix decomposition and successive interference cancellation, by which a significant complexity reduction can be achieved. Through simulations and complexity analysis, it is shown that a near-optimal performance is obtained by the authors proposed low-complexity bit-level LR-aided detector for the IDD in the MIMO systems.