Mm-Wave Massive MIMO Channel Estimation Supported by Higher-Order Markov Prior

Due to the large number of antennas in the antenna array, channel estimation for millimeter-wave (mm-Wave) massive MIMO becomes complex. Leveraging the sparsity of mm-Wave channels is an effective approach to reduce complexity and improve accuracy. For channel estimation methods that utilize the prior probability distribution of the sparse channel vector, the accuracy of the probability distribution is critical to the performance of channel estimation. This paper proposes a higher-order Markov prior model combined with the Turbo-OAMP framework, which is suitable for mm-Wave channel estimation scenarios where channel sparsity changes rapidly. Numerical simulation results show that the proposed method achieves better estimation accuracy and robustness in time-varying sparse mm-Wave channels.