Bilinear Approximate Message Passing Based Off-grid Channel Estimation for Multi-user Millimeter-Wave MIMO System

Massive multiple-input-multiple-output (MIMO) and millimeter-wave (mmWave) have been adopted as the enabling technologies for the 5G and beyond 5G (B5G) systems. However, due to the large number of antennas, it is hard to obtain the channel state information (CSI) which is essential for obtaining desirable beamforming gains. Off-grid error is one of the main limiting factors of the channel estimation (CE) performance, which presents when the true angle does not lie on the discretized angle grid of mmWave channel. To address this problem, we propose a joint algorithm named off-grid approximate message passing (OG-AMP) to achieve both angular domain CE and off-grid errors eliminationin in this paper. Specially, we formulate CE issue as a Bayesian inference problem to compute the posterior of the channel coefficients and adopt the Gaussian approximation to simplify the sum-product algorithm. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method.