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| Structured Sparse and Low Rank Channel Estimation in Uplink 3D-MIMO |
| LIU Kai FENG Hui YANG Tao HU Bo |
(Key Laboratory of EMW Information, Fudan University, Shanghai 200433, China)
(Department of Electronic Engineering, Fudan University, Shanghai 200433, China) |
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Abstract 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.
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Received: 02 May 2017
Published: 01 November 2017
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| Fund:The National Natural Science Foundation of China (61501124) |
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Corresponding Authors:
HU Bo
E-mail: bohu@fudan.edu.cn
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