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首页> 外文期刊>IEICE Transactions on fundamentals of electronics, communications & computer sciences >An Improved Quantization Scheme for Lattice-Reduction Aided MIMO Detection Based on Gram-Schmidt Orthogonalization
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An Improved Quantization Scheme for Lattice-Reduction Aided MIMO Detection Based on Gram-Schmidt Orthogonalization

机译:基于Gram-Schmidt正交化的格子减少辅助MIMO检测的改进量化方案

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摘要

Lattice-reduction (LR) technique has been adopted to improve the performance and reduce the complexity in MIMO data detection. This paper presents an improved quantization scheme for LR aided MIMO detection based on Gram-Schmidt orthogonalization. For the LR aided detection, the quantization step applies the simple rounding operation, which often leads to the quantization errors. Meanwhile, these errors may result in the detection errors. Hence the purpose of the proposed detection is to further solve the problem of degrading the performance due to the quantization errors in the signal estimation. In this paper, the proposed quantization scheme decreases the quantization errors using a simple tree search with a threshold function. Through the analysis and the simulation results, we observe that the proposed detection can achieve the nearly optimal performance with very low complexity, and require a little additional complexity compared to the conventional LR-MMSE detection in the high E_b/N_0 region. Furthermore, this quantization error reduction scheme is also efficient even for the high modulation order.
机译:已经采用格子缩减(LR)技术来提高性能并降低MIMO数据检测的复杂性。本文提出了一种改进的基于Gram-Schmidt正交化的LR辅助MIMO量化方案。对于LR辅助检测,量化步骤应用简单的舍入运算,这通常会导致量化误差。同时,这些错误可能导致检测错误。因此,提出的检测的目的是进一步解决由于信号估计中的量化误差而导致的性能下降的问题。在本文中,提出的量化方案使用带有阈值函数的简单树搜索来减少量化误差。通过分析和仿真结果,我们发现,与在高E_b / N_0区域中的常规LR-MMSE检测相比,所提出的检测可以以非常低的复杂度实现几乎最佳的性能,并且需要一点额外的复杂性。此外,即使对于高调制阶数,该量化误差减小方案也是有效的。

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