Variational Bayesian Channel Estimation for mmWave Massive MIMO-OFDM Systems

This paper proposes a novel channel estimation algorithm for mmWave massive MIMO-OFDM systems, named linear model based variational line spectral estimatio algorithm (LMVALSE). This algorithm can improve channel estimation performance by accurately estimating the angle of arrival (AoA), path delay with limited number of paths, thereby obtaining more accurate channel estimation. Specifically, the proposed method formulates the channel estimation problem as a linear model with unknown order and applies a message-passing based variational Bayesian framework for joint parameter and multi-path inference. By decoupling the complex estimation task into manageable subproblems and iteratively updating the posterior distributions, LMVALSE achieves higher accuracy and faster convergence. Simulation results demonstrate that the proposed algorithm outperforms state-of-the-art methods and exhibits robustness under varying system parameters.