Abstract
Uplink channel estimation is a classical problem for massive multiple-input multiple-output (MIMO) communication systems. Many uplink channel estimators are available in the literature, but they are usually sensitive to outliers. The channel estimation performance could degrade substantially if impulsive noise is not taken into account. In this letter, we try to combine the channel sparsity with the sparse property of impulsive noise and devise a fast variational Bayesian inference (VBI) method for uplink channel estimation in the presence of impulsive noise. The main novelty of the proposed method is to jointly estimate all the uplink channels by exploiting the common outliers among different users’ channels, which can significantly enhance the channel estimation performance. Numerical examples verify the effectiveness of the proposed method.
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