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An Efficient QRD-M Algorithm Using Partial Decision Feedback Detection

机译:基于部分决策反馈检测的高效QRD-M算法

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This paper presents a reduced-complexity QRDM algorithm using partial decision feedback (DF) detection. Adaptive QRD-M algorithm obtains the threshold value through the simulation to prune off paths at each stage. However, the proposed algorithm efficiently acquires the threshold value using partial DF detection at each stage. In 4 脳 4 V-BLAST system with 16-QAM, the complexity of the proposed algorithm is approximately 50 % lower than that of adaptive QRD-M algorithm at Eb/N0 = 16 dB. Moreover, the effectiveness of complexity reduction is especially predominant at low signal-to-noise ratio (SNR).
机译:本文提出了一种使用部分决策反馈(DF)检测的降低复杂度的QRDM算法。自适应QRD-M算法通过仿真获得阈值,以修剪每个阶段的路径。然而,提出的算法在每个阶段都使用部分DF检测来有效地获取阈值。在具有16-QAM的4×4 V-BLAST系统中,在Eb / N0 = 16 dB时,所提出算法的复杂度比自适应QRD-M算法低约50%。此外,在低信噪比(SNR)的情况下,降低复杂性的有效性尤为突出。

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