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A Probabilistic Model Based-Tracking Method for mmWave Massive MIMO Channel Estimation
DOI:10.1109/TVT.2023.3290207.png)
摘要
En 中文
Accurate channel estimation with low pilot overhead is vital to exploit full benefit of Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system. Although compressive sensing (CS) based algorithms could solve this problem, their performances are affected by grid mismatch. To overcome these issues, a probabilistic model taking the spatial and temporal correlations into account for the massive MIMO is proposed in this correspondence. With this model, a quasi on-grid method is proposed to solve the problem of grid mismatch with low computational complexity. Finally, we integrate it into Turbo-CS framework and develop a message passing algorithm to solve the estimation problem. Simulation results reveal the superiority of proposed algorithm in estimation accuracy and tracking ability.
Keyword:
Grid mismatch
channel estimation
massive MIMO
probabilistic model
期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
机构
引用论文
Off-Grid Compressive Channel Estimation for mm-Wave Massive MIMO With Hybrid Precoding基于混合预编码的毫米波大规模MIMO离网压缩信道估计

