Channel Estimation for Millimeter Wave Wideband Massive MIMO Systems via Tensor Decomposition

Abstract

The acquisition of channel state information is crucial in massive multiple-input multiple-output (MIMO) systems when large scale antenna array is used. For Millimeter Wave (mmWave) wideband massive MIMO-OFDM systems, both the number of antennas and subcarriers are very large, so it is very difficult for us to get accurate channel information. In this paper, we propose a tensor-based channel estimation scheme for mmWave wideband channels. Firstly, we transform the two- dimensional mmWave wideband channel matrix into a three-dimensional tensor due to the large number of antennas and subcarriers. Secondly, by utilizing the PARAFAC decomposition of the tensor, the estimated three factor matrices can be obtained. Then, channel parameters can be extracted from the estimated factor matrices. Simulation results show that our proposed method outperforms the conventional low complexity compressed sensing based method, such as orthogonal matching pursuit (OMP) method, while maintaining the same complexity order.