Channel Estimation for Hybrid MIMO Systems With Array Model Errors and Beam Squint Effects

This paper proposes a channel estimation method for wideband hybrid multiple-input-multiple-output (MIMO) systems operating in high-frequency bands, including millimeterwave (mmWave) and sub-terahertz (sub-THz). The proposed method accounts for beam squint effects and array errors, which arise from hardware impairments and time-varying environmental factors, such as thermal effects and dynamic motion of the array. Although conventional channel estimation methods calibrate array errors through offline operation with large training pilots, the calibration errors remain due to time-varying array errors. Therefore, the proposed channel estimation method calibrates array errors online with small pilot overhead. In the proposed method, array response matrices are explicitly decomposed into a small number of physical parameters, including path gains, angles, delays, and array errors, which are iteratively estimated by alternating optimization based on a maximum likelihood (ML) criterion. To enhance the convergence performance, we introduce a switching mechanism from an on-grid algorithm to an off-grid algorithm depending on the estimation accuracy of the array error during algorithmic iterations. Furthermore, we introduce an approximate mutual coupling model to reduce the number of parameters. The reduction of parameters not only lowers computational complexity but also mitigates overfitting to noisy observations. Numerical simulations demonstrate that the proposed method works effectively online in the presence of array errors even with small pilot overhead.