Abstract

The mobile Internet business is rapidly developing, leading to a demand for higher data service rates. To address this, massive Multiple-Input Multiple-Output (MIMO) technology has gained widespread attention due to its ability to fully exploit spatial degree of freedom and improve spectral efficiency while maintaining high energy efficiency. However, there are challenges with channel estimation in multi-user massive MIMO systems, such as pilot overhead, accuracy, and complexity. To tackle these challenges, this paper proposes a highly demanding beam Domain Decomposition (DD) and Singular Value Decomposition (SVD) method-based channel estimation methodology. By dividing into various single-user MIMO systems, the multi-user massive MIMO system, the proposed approach models the beam domain channel. The channel autocorrelation matrix is optimized using the SVD method, which lowers pilot overhead and estimates error while increasing computing efficiency. The suggested approach also provides closed-form analytical formulations for the calculated error covariance matrix. The numerical outcomes show that the suggested algorithm outperforms conventional schemes in performance. Therefore, the proposed algorithm could provide an effective solution for channel estimation in multi-user massive MIMO systems, which is increasingly critical as the demand for high data rates in the mobile Internet business continues to grow.© 2017 Elsevier Inc. All rights reserved.

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