| Citation: | Xinhua LU, Carles Navarro MANCHÓN, Zhongyong WANG, Chuanzong ZHANG. Channel Estimation Algorithm Using Temporal-spatial Structure for Up-link of Massive MIMO Systems[J]. Journal of Electronics & Information Technology, 2020, 42(2): 519-525. doi: 10.11999/JEIT180676
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To deal with the estimation problem of non-stationary channel in massive Multiple-Input Multiple-Output (MIMO) up-link, the 2D channels’ sparse structure information in temporal-spatial domain is used, to design an iterative channel estimation algorithm based on Dirichlet Process (DP) and Variational Bayesian Inference (VBI), which can improve the accuracy under a lower pilot overhead and computation complexity. On account of that the stationary channel models is not suitable for massive MIMO systems anymore, a non-stationary channel prior model utilizing Dirichlet Process is constructed, which can map the physical spatial correlation channels to a probabilistic channel with the same sparse temporal vector. By applying VBI technology, a channel estimation iteration algorithm with low pilot overhead and complexity is designed. Experiment results show the proposed channel method has a better performance on the estimation accuracy than the state-of-art method, meanwhile it works robustly against the dynamic system key parameters.
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