A Novel SAGE Algorithm for Estimating Parameters of Wideband Spatial Nonstationary Wireless Channels With Antenna Polarization
Z. Y. Zhou, Cheng‐Xiang Wang, Li Zhang, Jie Huang, Lijian Xin, El‐Hadi M. Aggoune, Yang Miao
Abstract
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.