A Low-Complexity Channel Estimation Method Based on Subspace for Large-Scale MIMO Systems

Abstract

In large-scale multiple-input multiple-output (LS-MIMO) systems, singular value decomposition (SVD) or eigenvalue decomposition (EVD) are common channel estimation schemes. However, the computational complexity of two estimators limits the application in LS-MIMO systems. Motivated by this, in order to reduce the complexity, a novel method that combines fast single compensation approximated power iteration (FSCAPI) algorithm with iterative least square with projection (ILSP), FSCAPI-ILSP, is proposed in this paper, In the proposed method, the received signals subspace is estimated by the FSCAPI algorithm firstly, then the initial channel estimation is obtained by the pilot signals. Finally, we combine it with the ILSP algorithm to improve the accuracy of the channel estimation. Compared with the conventional methods, the proposed scheme degrades the computational complexity significantly. Simulated results indicate the provided method is better than its counterparts and improves the channel estimation accuracy effectively.