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The problem of optimal likelihood based modulation classification (MC) for optimal detection in 2x2 multiuser MIMO (MU-MIMO) receivers is considered. The optimal Log-MAP classifier is computationally exhaustive, and its sub-optimal Max-Log-MAP version poses remarkable degradation in performance. Between these two extremes, we propose four computationally simplified methods for MC, by taking special subsets of Euclidean distance computations that constitute the decision metric.

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In this paper, dual layer multiple-input multiple-output (2x2 MIMO) systems that use the 1024-QAM modulation are studied. We build on the layered orthogonal lattice detector (LORD), which achieves optimal maximum-likelihood (ML) performance, but which has high complexity with 1024-QAM, and argue that the low-complexity version of LORD (LC-LORD) introduces a significant performance degradation, especially with high channel correlation. We propose several approaches that outperform LC-LORD at a lower complexity.

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