Joint Multipath Channel Estimation and Array Channel Inconsistency Calibration for Massive MIMO Systems

Efficient communication in massive multiple-input multiple-output (MIMO) systems relies on accurate channel estimation to optimize signal transmission efficiency, reliability, and minimize interference and power consumption. However, the presence of non-uniform array gain-phase perturbations among antenna elements poses practical challenges, degrading the precision of estimation. In response, this paper introduces a parameterized joint angle and delay estimation (JADE) method tailored for multipath channel estimation in fully uncalibrated arrays within massive MIMO systems. Our innovative spatial and frequency-based co-smoothing method is proposed to construct a rank-recovered data covariance matrix, enhancing the system’s ability to distinguish coherent multipath signals. The JADE method employs a one-dimensional angular spectrum and delay spectrum search under the principle of rank reduction, providing a closed-form solution for array gain-phase perturbation estimates. The deterministic Cramér-Rao lower bound for the proposed model is derived. Numerical simulations affirm the method’s superior performance. In conclusion, our approach addresses the demand for precise channel estimation in low signal-to-noise ratio scenarios, particularly benefiting Internet of Things (IoT) applications.