Abstract
A novel low-complexity decision-feedback detection algorithm with constellation constraints (DFCC) is proposed for multi-input-multi-output (MIMO) systems. An enhanced interference cancellation is achieved by introducing multiple constellation points as decision candidates. A complexity reduction strategy is also developed to avoid redundant processing with reliable decisions. For time-varying channels, the proposed receiver updates the filter weights using a recursive least-squares (RLS)-based algorithm. This efficient detector is also incorporated in a multiple-branch (MB) structure to achieve a higher detection diversity order. A soft-output DFCC detector is also proposed as a component of an iterative detection and decoding receiver scheme. Simulations show that the proposed DFCC technique has complexity as low as the adaptive decision-feedback (DF) detector while it significantly outperforms ordered successive interference cancellation (OSIC) processing.
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