A Multiuser CQI Prediction Scheme with Channel Estimation Error in the Massive MIMO Networks

2018 ◽  
Author(s):  
Bin Wang ◽  
Yongyu Chang ◽  
Minshan Xiang ◽  
Jingzhou Wu
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Mimo Networks ◽  
Prediction Scheme

scholarly journals Interference Suppression in Heterogeneous Massive MIMO Systems with Imperfect CSI

2021 ◽  
Author(s):  
Rana Sedghi ◽  
masoumeh azghani
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Error ◽  
Interference Management ◽  
Small Cells ◽  
Channel Estimation Error ◽  
Zero Forcing ◽  
Channel State ◽  
Error Matrix ◽  
Mimo Networks

Abstract Interference management is of paramount importance in heterogeneous massive mimo networks (HetNet). In this paper, an algorithm has been suggested to suppress the interference in large-MIMO HetNets with imperfect channel state information(CSI). The proposed technique controls both the intra-tier and cross-tier interference of the macrocell as well as the small cells. The intra-tier interference of the macrocell as well as the cross-tier interference have been minimized under maximum transmission power and minimum signal to interference and noise ratio (SINR) constraint. The channel estimation error matrix has also been modeled using the joint sparsity property. The precoding algorithm is thus achieved through the application of semi-definite relaxation and block coordinate descent techniques. The intra-tier interference of the small cells are addressed with the aid of the zero forcing scheme. The proposed method has been validated through various simulations which confirm the superiority of the algorithm over its counterparts.

scholarly journals Exploiting the Massive MIMO Channel Structural Properties for Minimization of Channel Estimation Error and Training Overhead

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 32434-32452 ◽  
Author(s):  
Samer Bazzi ◽  
Stelios Stefanatos ◽  
Luc Le Magoarou ◽  
Salah Eddine Hajri ◽  
Mohamad Assaad ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Structural Properties ◽  
Massive Mimo ◽  
Estimation Error ◽  
Mimo Channel ◽  
Channel Estimation Error ◽  
And Training

scholarly journals Massive MIMO Performance With Imperfect Channel Reciprocity and Channel Estimation Error

2017 ◽  
Vol 65 (9) ◽  
pp. 3734-3749 ◽  
Author(s):  
De Mi ◽  
Mehrdad Dianati ◽  
Lei Zhang ◽  
Sami Muhaidat ◽  
Rahim Tafazolli
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Channel Reciprocity

scholarly journals Channel Rectification and Signal Estimation Based on EIV Model in Massive MIMO System

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Liang Zhong ◽  
Li Huang ◽  
Zhengmin Kong
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Channel Model ◽  
Least Squares Method ◽  
Mimo System ◽  
Estimation Error ◽  
Estimation Algorithm ◽  
Channel Estimation Error ◽  
Signal Estimation ◽  
Pilot Contamination

The performance of Massive MIMO is severely limited by channel estimation error, which is caused by pilot contamination and channel aging. In this paper, we propose an estimation algorithm based on the weighted total least-squares method with errors-in-variables (EIV) model to alleviate the influence of pilot contamination and channel aging. Then, a channel rectification method has been investigated to diminish the inaccuracy of channel estimation. Comparing with the traditional methods, it not only helps to make the signal estimation more accurate, but also provides opportunities to correct the channel model with estimation error and update the aged channel statement information. Simulations are provided to verify the efficacy of this method.

Influence of Channel Estimation Error on MIMO Multiplexing Using Precoding in Downlink OFDM Radio Access

2009 ◽  
Vol E92-B (5) ◽  
pp. 1553-1562
Author(s):  
Takashi ISOGAI ◽  
Mamoru SAWAHASHI ◽  
Hidekazu TAOKA ◽  
Kenichi HIGUCHI
Keyword(s):  
Channel Estimation ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Radio Access
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