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Channel Estimation for Massive MIMO Uplink Transmission over Frequency Selective Fading Channels

In this paper, a low-complexity compressive channel estimation method is proposed for massive multiple-input multiple-output (MIMO) uplink transmission over frequency selective fading channels. Based on the physical channel model, the structured sparsity in the beam-delay domain is investigated and the overcomplete discrete Fourier transform matrix is utilized to mitigate channel power leakage in the beam-delay domain. Specifically, a nonorthogonal uplink pilot design scheme is employed to reduce the pilot overhead, then the compressive sensing model is established. By exploiting the structured sparsity and energy concentration property of the beam-delay domain channel, the energy-concentration based channel estimation algorithm is proposed by utilizing the sparsity level of channels. Simulation results demonstrate that the newly proposed algorithm outperforms other existing estimators with relatively low complexity.