Abstract

Obtaining accurate channel state information (CSI) is an important prerequisite for achieving good performance of the Massive MIMO system. The traditional pilot-based channel estimation algorithm has low spectrum utilization. The channel estimation algorithm based on compressed sensing can make full use of the sparsity of the channel and realize channel estimation with fewer pilots. In this paper, wavelet denoising is combined with a sparse channel estimation algorithm based on Orthogonal Matching Pursuit (OMP), and Cramer-Rao Lower Bound (CRLB) is derived. The simulation results show that this method has better performance.

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