A Parallelized Algorithm for Channel Estimation in mmWave Massive MIMO Communications

Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) technology is considered as a key feature for 5G and B5G systems because of its extensive spectrum resources. Accurately and timely estimating the channel state information (CSI) is critical for guaranteeing the effective signal transmission. In this paper, we propose an algorithm called Sparse Accelerated projection consensus (SAPC) to estimate the mmWave massive MIMO channel in a parallel computing way, which should be suitable for FPGA and ASIC implementations. Also, SAPC takes into account the sparsity of the channel to reduce the complexity.