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This letter considers the problem of channel estimation for millimeter wave (mmWave) multiple-input multiple-output systems under a transmitter impairments model. Specifically, taking the transmitter hardware impairments into account, the performance of conventional pilots-based channel estimation scheme will be degraded due to the destroyed training pilots. By exploiting the sparsity of mmWave channel in the angular domain, a new channel estimation algorithm based on the Bayesian compressive sensing (BCS) and least square estimation (LSE) is proposed. First, the expectation maximization algorithm is presented to solve the BCS problem, and the refined measurement matrix and the support of the channel vector are obtained. Next, the channel gain coefficients are estimated by using the LSE. Simulation results show that the proposed algorithm can achieve better performance compared with the conventional BCS and orthogonal matching pursuit algorithm.
Wu et al. (Fri,) studied this question.