| 基于随机网格张量分解的多用户毫米波大规模MIMO系统信道估计 |
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| 引用本文： | 张景,周小平,王培培,李莉.基于随机网格张量分解的多用户毫米波大规模MIMO系统信道估计[J].上海师范大学学报(自然科学版),2021,50(1):108-114. |
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| 作者姓名： | 张景 周小平 王培培 李莉 |
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| 作者单位： | 上海师范大学 信息与机电工程学院, 上海 200234,上海师范大学 信息与机电工程学院, 上海 200234,上海师范大学 信息与机电工程学院, 上海 200234,上海师范大学 信息与机电工程学院, 上海 200234 |
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| 基金项目： | 上海市科委地方院校能力建设项目（19070502900） |
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| 摘 要： | 利用毫米波信道的稀疏散射特性和张量的空间结构,提出了一种随机网格张量分解的信道估计方法,接收信号被表示为一个四阶张量,采用随机张量压缩对单个用户信道进行解耦;采用网格张量分解方式,将大尺度的用户信道张量分解为若干个小尺度张量,并行且独立地分解所有子张量,由相关因子矩阵估计信道参数.仿真结果表明,该算法能获得较为准确的信道参数估计,有效地降低了信道估计算法的复杂度.
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| 关 键 词： | 毫米波 多用户大规模多输入多输出(MIMO) 信道估计 随机网格张量分解 |
| 收稿时间： | 2020/9/7 0:00:00 |
Channel estimation of multi-user millimeter wave massive MIMO system based on random grid tensor decomposition |
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| ZHANG Jing,ZHOU Xiaoping,WANG Peipei and LI Li.Channel estimation of multi-user millimeter wave massive MIMO system based on random grid tensor decomposition[J].Journal of Shanghai Normal University(Natural Sciences),2021,50(1):108-114. |
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| Authors: | ZHANG Jing ZHOU Xiaoping WANG Peipei and LI Li |
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| Institution: | College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China,College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China,College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China and College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China |
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| Abstract: | By using the sparse scattering characteristics of the millimeter wave channel and the spatial structure of the tensor, a channel estimation method based on random grid tensor decomposition was proposed. The received signal was represented as a fourth-order tensor and the user channel was decoupled by random tensor compression. After that, using grid tensor decomposition method, the large-scale user channel tensor was decomposed into several small-scale tensors, by which all sub-tensors are decomposed in parallel and independently, and the channel parameters were estimated according to the correlation factor matrix. The simulation results showed that the algorithm was able to obtain more accurate channel parameter estimation, which reduced the complexity of the channel estimation algorithm effectively. |
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| Keywords: | millimeter wave multi-user massive multiple input and multiple output(MIMO) channel estimation random grid tensor decomposition |
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