一种网格约简辅助MIMO检测的排序反馈非线性量化算法

Yanhua Sun, Hao Wang, Yan-hua Zhang
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引用次数: 0

摘要

近年来,晶格约简技术已被证明可以提高MIMO系统的性能,但由于信号变换引起的星座偏分布,优化量化算法的复杂度较高。本文提出了一种排序反馈非线性量化(SFQ)方案,该方案考虑了变换星座的边界和信号要素之间的相关性,并根据量化误差选择要素进行量化。仿真结果表明,基于所提量化方案的LRA MIMO探测器的性能优于基于非排序反馈和独立元素量化方案的LRA MIMO探测器。该算法可以在多项式复杂度下接近平坦块衰落信道中最大似然检测的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Sorted Feedback Non-linear Quantization Algorithm for Lattice Reduction Aided MIMO Detection
Lattice reduction technology has been proved to improve MIMO system performance recently, but the complexity of optimum quantization algorithm is high due to constellation biased distribution caused by signal transformation. In this paper, a sorted feedback non-linear quantization (SFQ) scheme is proposed, which considers both the border of transformed constellation and the correlations between signal elements, and the elements are selected to be quantized according to quantization errors. The simulation results show that the performance of lattice reduction aided (LRA) MIMO detectors based on the proposed quantization scheme is superior to that of LRA MIMO detectors based on non-sorted feedback and independent element-wise quantization schemes. The proposed algorithm can approach the performance of maximum likelihood detection in polynomial complexity in a flat block fading channel.
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