A Fast Tensor-Based Channel Estimation Method in mmWave Massive MIMO-OFDM Systems

In this paper, we focus on the channel parameter estimation issue for millimeter wave (mmWave) massive multi-user multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Exploiting the sparse scattering characteristic of the mmWave channel and multidimensional stucture, we propose a fast tensor-based channel estimation method. The proposed algorithm derives a real-valued PARAFAC tensor signal model by applying the forward-backward technology and unitary transformation. Compared with the traditional parallel factor (PARAFAC)-based algorithm, the proposed method provides a higher parameter estimation accuracy and lower computational complexity. Simulation results show the effectiveness of the proposed channel estimation algorithm.