scholarly journals Initial Results on Deep Learning-Based Pilot Contamination Mitigation in Massive MIMO Systems

2019 ◽  
Author(s):  
Felipe Augusto Pereira de Figueiredo
Keyword(s):  
Deep Learning ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Wireless Channels ◽  
Mimo Systems ◽  
Mimo Channel ◽  
Training Phase ◽  
Pilot Contamination ◽  
Extensive Training ◽  
Initial Results

In this brief letter we report our initial results on the application of deep-learning to the massive MIMO channel estimation challenge. We show that it is possible to estimate wireless channels and that the possibility of mitigating pilot-contamination with deep-learning is possible given that the leaning model underwent an extensive training-phase and that it has been presented with a large number of different channel conditions.

scholarly journals Massive MIMO channel estimation considering pilot contamination and spatially correlated channels

2020 ◽  
Vol 56 (8) ◽  
pp. 410-413
Author(s):  
F.A. Pereira de Figueiredo ◽  
D.A. Mendes Lemes ◽  
C. Ferreira Dias ◽  
G. Fraidenraich
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Channel ◽  
Pilot Contamination ◽  
Spatially Correlated ◽  
Correlated Channels ◽  
Spatially Correlated Channels

Deep Learning-Based Beamspace Channel Estimation in mmWave Massive MIMO Systems

2020 ◽  
Vol 9 (12) ◽  
pp. 2212-2215
Author(s):  
Yinghui Zhang ◽  
Yifan Mu ◽  
Yang Liu ◽  
Tiankui Zhang ◽  
Yi Qian
Keyword(s):  
Deep Learning ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems

scholarly journals Channel Estimation for Massive MIMO Systems

2022 ◽  
Vol 10 (1) ◽  
pp. 137-138
Author(s):  
Polireddi Sireesha
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo Channel ◽  
Normal System ◽  
Performance Tests ◽  
Beam Search ◽  
Search System ◽  
Multiple Beams ◽  
High Level

Abstract: In MIMO millimeter-wave (mmWave) systems, while the hybrid digital/analog precoding structure provides the ability to increase the reach rate, it also faces the challenge of reducing the channel time limit due to the large number of horns on both sides of the Tx / Rx. . In this paper, channel measurement is done by searching with multiple beams, and a new hierarchical multi-beam search system is proposed, using a pre-designed analog codebook. Performance tests show that, compared to a highperformance system, the proposed system not only achieves a high level of success in getting multiple beams under normal system settings but also significantly reduces channel estimation time Keywords: Massive MIMO, Channel Estimation, precoding

scholarly journals A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 218 ◽  
Author(s):  
Kifayatullah Bangash ◽  
Imran Khan ◽  
Jaime Lloret ◽  
Antonio Leon
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Least Square ◽  
Mimo Channel ◽  
Finite Sample ◽  
The Impact

Traditional Minimum Mean Square Error (MMSE) detection is widely used in wireless communications, however, it introduces matrix inversion and has a higher computational complexity. For massive Multiple-input Multiple-output (MIMO) systems, this detection complexity is very high due to its huge channel matrix dimension. Therefore, low-complexity detection technology has become a hot topic in the industry. Aiming at the problem of high computational complexity of the massive MIMO channel estimation, this paper presents a low-complexity algorithm for efficient channel estimation. The proposed algorithm is based on joint Singular Value Decomposition (SVD) and Iterative Least Square with Projection (SVD-ILSP) which overcomes the drawback of finite sample data assumption of the covariance matrix in the existing SVD-based semi-blind channel estimation scheme. Simulation results show that the proposed scheme can effectively reduce the deviation, improve the channel estimation accuracy, mitigate the impact of pilot contamination and obtain accurate CSI with low overhead and computational complexity.

scholarly journals Massive MIMO Channel Estimation Considering Pilot Contamination and Spatially Correlated Channels

2019 ◽  
Author(s):  
Felipe Augusto Pereira de Figueiredo ◽  
Dimas A. M. Lemes ◽  
Claudio Ferreira Dias ◽  
Gustavo Fraidenraich
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Massive Mimo ◽  
Mimo Channel ◽  
Mean Square ◽  
Pilot Contamination ◽  
Spatially Correlated ◽  
Correlated Channels ◽  
Spatially Correlated Channels ◽  
The Impact

In this letter, we present a study on linear channel estimators and their respective mean square error (MSE) expressions acknowledging spatially correlated channels and pilot contamination. We also investigate the impact of imperfect channel covariance matrix knowledge.

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