Structured Sparse and Low Rank Channel Estimation in Uplink 3D-MIMO

被引：1
作者：
Liu Kai
Feng Hui
Yang Tao
Hu Bo [1 ]
机构：
[1] Fudan Univ, Key Lab EMW Informat, Shanghai 200433, Peoples R China
来源：
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY | 2018年 / 40卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Channel estimation; 3D-MIMO; Structured sparseness; Low rank; Matching pursuit;
D O I：
10.11999/JEIT170399
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Three Dimension Multi-Input Multi-Output (3D-MIMO) systems can effectively improve frequency efficiency and system capacity. However, with the growing number of antennas and users, pilot sequences are non-orthogonal, which will affect the accuracy of 3D-MIMO channel estimation and increase complexity. In this paper, the structured sparseness and low rank property of 3D-MIMO channel are studied. By taking advantage of these properties, a channel estimation algorithm is proposed, and the convergence and complexity of the algorithm are analyzed. Simulation results verify that the proposed algorithm can accurately recover 3D-MIMO channel with low complexity.
引用
收藏
页码：116 / 122
页数：7
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