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Maximum-Likelihood Detection (MLD) is the optimal scheme for Multiple-Input Multiple-Output (MIMO) channels. However, due to its exponentially high complexity, many alternative algorithms, including some Parallel Detection (PD) ones with low complexity and high stability, have been proposed for practical applications. Nevertheless, the existing PD algorithms are unable to exploit sufficiently the diversity order increment for low-complexity algorithms via MLD for partial layers; consequently, the complexity of the sub-detectors is still undesirably high. In this paper, a novel PD algorithm with relative low-complexity sub-detectors, i.e., the partial decision feedback sub-detectors, has been developed.
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