A Novel SAGE Algorithm for Estimating Parameters of Wideband Spatial Nonstationary Wireless Channels With Antenna Polarization

In this article, a novel space-alternating generalized expectation–maximization (SAGE) algorithm is proposed for parameter estimations of wideband spatial nonstationary wireless channels with antenna polarization (SAGE-WSNSAP). Compared with the traditional SAGE algorithm, the proposed SAGE-WSNSAP algorithm adds spatial nonstationarity by introducing birth–death coefficients at both transmitter (Tx) and receiver (Rx) sides into the parametric model. To reduce the complexity of the SAGE-WSNSAP algorithm, a coarse-to-fine search method is adopted in the initialization step. In addition, multiple-input multiple-output (MIMO) channel measurements are conducted to validate the proposed algorithm. The measurement results of the angle-delay power spectral density (PSD) and average delay PSD are compared with those estimated by the far-field SAGE algorithm, the near-field SAGE algorithm, and the proposed algorithm. It is found that the estimation results using the proposed SAGE-WSNSAP algorithm show higher similarity to measurement results than using the other two SAGE algorithms. In comparison to the far-field and near-field SAGE algorithms, the SAGE-WSNSAP algorithm can extract more effective multipath components (MPCs) and improve the power extraction ratios.