Compressed sensing-based structured joint channel estimation in a multi-user massive MIMO system

2017 ◽  
Vol 18 (12) ◽  
pp. 2082-2100 ◽  
Author(s):  
Ruo-yu Zhang ◽  
Hong-lin Zhao ◽  
Shao-bo Jia
Keyword(s):  
Channel Estimation ◽  
Compressed Sensing ◽  
Massive Mimo ◽  
Mimo System ◽  
Joint Channel

scholarly journals An Improved Multicell MMSE Channel Estimation in a Massive MIMO System

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ke Li ◽  
Xiaoqin Song ◽  
M. Omair Ahmad ◽  
M. N. S. Swamy
Keyword(s):  
Channel Estimation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo System ◽  
Computational Cost ◽  
Spectrum Efficiency ◽  
Performance Simulation ◽  
Estimation Scheme ◽  
Joint Channel

Massive MIMO is a promising technology to improve both the spectrum efficiency and the energy efficiency. The key problem that impacts the throughput of a massive MIMO system is the pilot contamination due to the nonorthogonality of the pilot sequences in different cells. Conventional channel estimation schemes cannot mitigate this problem effectively, and the computational complexity is increasingly becoming larger in views of the large number of antennas employed in a massive MIMO system. Furthermore, the channel estimation is always carried out with some ideal assumptions such as the complete knowledge of large-scale fading. In this paper, a new channel estimation scheme is proposed by utilizing interference cancellation and joint processing. Highly interfering users in neighboring cells are identified based on the estimation of large-scale fading and then included in the joint channel processing; this achieves a compromise between the effectiveness and efficiency of the channel estimation at a reasonable computational cost, and leads to an improvement in the overall system performance. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

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