Abstract
In massive MIMO systems, the channel shows a spatial non-stationarity that has a significant impact on the design of sparse channel estimation scheme based on compressive sensing, due to the large size of antenna array. In this letter, the block matching pursuit (BMP)-based two-stage sparse channel estimation scheme is proposed for spatial non-stationary (SNS) channels. In this scheme, the BMP is introduced to search for the support blocks and the threshold-based denoising method is utilized to refine the supports of non-zero elements. In order to evaluate our scheme, we provide a simple SNS channel model modified from the 3GPP 3D channel model to capture the delay-domain special sparse characteristic. Simulation results demonstrate that the proposed scheme can recover channels effectively and achieve better performance than comparison methods.
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