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- W2809538140 abstract "Two new approaches to reduce the computational complexity of the orthogonal real valued decomposition (ORVD) Trellis based multiple-input multiple-output (MIMO) detection algorithm for iterative receiver systems, together with two methods to effectively limit the dynamic range of the internal path metric values, which are central to the algorithm, are presented in this paper. Simulations results for four different channel models show that no communications performance loss incurs, while requiring around 23% less metric evaluations (i.e., visited nodes). A histogram analysis demonstrates the effectiveness of the dynamic-range-limiting prior term regularization and path metric normalization, applied to the originally unbounded metric value distribution. The regularized and normalized metric is non-negative, i.e., lower bounded by zero, the value distribution is shifted closer to zero, and we cut off large values that have no influence on the communications performance." @default.
- W2809538140 created "2018-06-29" @default.
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- W2809538140 date "2018-03-01" @default.
- W2809538140 modified "2023-09-25" @default.
- W2809538140 title "Reducing the Computational Complexity of ORVD-Trellis Search Based MIMO Detection" @default.
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- W2809538140 doi "https://doi.org/10.1109/iccnc.2018.8390383" @default.
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