| 大规模MIMO系统中低复杂度的稀疏信道估计 |
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| 引用本文： | 方昕,刘云驹,曹海燕,潘鹏.大规模MIMO系统中低复杂度的稀疏信道估计[J].电信科学,2016,32(5):89-95. |
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| 作者姓名： | 方昕 刘云驹 曹海燕 潘鹏 |
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| 作者单位： | 杭州电子科技大学通信工程学院，浙江 杭州 310018 |
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| 基金项目： | 国家自然科学青年基金资助项目(61501158)，浙江省自然科学基金资助项目(LY14F010019)，浙江省固态存储和数据安全关键技术重点科技重新团队项目(2013TD03)，The National Natural Science Foundation of China for Youths(61501158)，The Natural Science Foundation of Zhejiang Province(LY14F010019)，Solid State Storage and Data Security Key Technology of Zhejiang Province(2013TD03) |
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| 摘 要： | 针对大规模多输入多输出（MIMO）系统信道估计算法复杂度高的缺陷，结合无线通信信道固有的稀疏性提出了一种低复杂度的稀疏信道估计算法。该算法是在传统的离散傅里叶变换（DFT）信道估计的基础上利用分离算法将信道抽头与噪声空间分离开来，使得信道估计时只需要计算信道抽头的部分，因此算法的计算复杂度被大大降低。仿真结果表明，该算法在保持低复杂度的同时，可获得接近最小均方误差（MMSE）性能。
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| 关 键 词： | 大规模MIMO 信道估计 稀疏性 算法复杂度 |
Low-complexity sparse channel estimation for massive MIMO systems |
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| Xin FANG,Yunju LIU,Haiyan CAO,Peng PAN.Low-complexity sparse channel estimation for massive MIMO systems[J].Telecommunications Science,2016,32(5):89-95. |
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| Authors: | Xin FANG Yunju LIU Haiyan CAO Peng PAN |
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| Affiliation: | School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China |
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| Abstract: | Due to the high computational complexity of massive MIMO system,a low-complexity sparse channel estimation algorithm was proposed utilizing the inherent sparsity of the wireless communication channel to improve the estimation performance.The proposed algorithm separated channel tap from noise space based on the traditional discrete Fourier transform by adopting integral separation algorithm.This channel estimation algorithm need only calculate the channel tap,thus markedly reducing complexity of the algorithm.Numerical simulations show that proposed algorithm can approach to the performance of the minimum mean-square error estimator while maintaining lower complexity. |
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| Keywords: | massive MIMO channel estimation sparsity algorithm complexity |
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