Efficient Channel Estimation for mmWave MIMO With Transceiver Hardware Impairments

Transceiver hardware impairments (e.g., phase noise, high power amplifier nonlinearities, in-phase/quadrature-phase imbalance, and quantization errors) degrade the performance of channel estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Although compensation methods can be exploited to mitigate the impact of hardware impairments, there always remains residual impairments that will distort the training pilots and received signals. In this paper, we reformulate the channel estimation with transceiver impairments into a sparse recovery problem from a Bayesian perspective and propose an efficient channel estimation algorithm. The proposed algorithm can effectively deal with the perturbation in channel estimation problem caused by the transmitter hardware impairments with small amount computation times. Simulation results demonstrate the superior performance of the proposed algorithm compared to the conventional orthogonal matching pursuit algorithm (OMP) based channel estimation method and Bayesian inference method.