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In this paper, we study the channel estimation problem for the millimeter wave (mm-wave) hybrid massive multiple-input multiple-output (MIMO) system. Based on the sparsity exhibited by the mm-wave channel in the angular domain, we select a portion of the beams that contribute to the communication process from the beamspace. Then, only the channel coefficients in the selected beamspace need to be estimated. The channel estimation problem is converted into a sparse signal reconstruction problem and solved by employing the generalized approximate message passing (GAMP) algorithm with Laplace distribution. The scale parameter of distribution is designed by analyzing the variance of the partial channel coefficients. Because only the partial channel coefficients need to be estimated, the computational complexity of the proposed GAMP approach is much lower than other methods. Simulation results show that the proposed channel estimation scheme exhibits significant advantages both in terms of estimation accuracy and spectral efficiency.

Channel estimation via GAMP for millimeter wave hybrid massive MIMO systems