| 摘要: |
| 提出了一种改进的Tucker分解法，将二维的张量分解到两个维度中.分别通过改进Tucker和Tucker算法的矩阵减秩和收敛运算，得到保存完整信息的原张量的近似估计值.仿真实验结果表明，改进Tucker算法提高了系统的检测性能. |
| 关键词: 大规模MIMO 张量分解 数据检测 Tucker算法 |
| DOI：10.3969/J.ISSN.1000-5137.2017.01.013 |
| 分类号: |
| 基金项目:上海市自然基金项目（16ZR1424500） |
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| The detection algorithm based on low rank tensor decomposition of large-scale MIMO |
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Liu Xingyue, Zhou Xiaoping, Li Li, Peng Zhangjie
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College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
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| Abstract: |
| In this paper,we propose an improved Tucker decomposition algorithm.The tensor is decomposed into two dimensions.By using matrix rank reduction and convergence in both Tucker and improved Tucker algorithm,we get an approximate estimation which can preservewhole information of original tensor completely.The simulation result shows that the improved Tucker decomposition algorithm can enhance the performance of the error detection of the system. |
| Key words: massive MIMO tensor decomposition data detection Tucker algorithm |
