Structured Sparse Channel Estimation for 3D-MIMO Systems

被引：2
作者：
Liu, Kai [1 ]
Feng, Hui [1 ]
Yang, Tao [1 ]
Hu, Bo [1 ,2 ]
机构：
[1] Fudan Univ, Sch Informat Sci & Engn, Res Ctr Smart Networks & Syst, Shanghai 200433, Peoples R China
[2] Fudan Univ, Key Lab EMW Informat MoE, Shanghai 200433, Peoples R China
来源：
2016 IEEE 83RD VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING) | 2016年
关键词：
Massive; 3D-MIMO; structured sparseness; common support; channel estimation; MIMO;
D O I：
10.1109/VTCSpring.2016.7504492
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：
In this paper, a low-complexity sparse channel estimation scheme is proposed for massive three dimensional multiinput multi-output (3D-MIMO) systems. In outdoor propagation environment, 3D-MIMO channels exhibit joint sparseness in both temporal and angular domains, sharing the common support in delay domain. By taking prior knowledge of the structured sparseness, the proposed heuristic channel estimation method can greatly reduce the complexity of channel estimation, and achieve a near optimal performance. Simulation results verify the effectiveness of the proposed algorithm.
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页数：6
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