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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.