Channel Parameter Estimation and Localization for Near-Field XL-MIMO Communications

In this letter, we propose an effective near-field channel parameter estimation and localization algorithm for extremely large-scale multiple-input multiple-output (XL-MIMO) systems. Exploiting the structural relation between the parameters and near-field codebook matrices, the proposed algorithm first implements the preliminary extraction of near-field channel parameters. Subsequently, the obtained parameters, including angles, distances and propagation gains, are further optimized by the iterative refinement. Localization of user and scattering points in near-field region can be achieved utilizing the obtained high-precision parameters. In addition, we provide the derivation process of Cramér-Rao bound (CRB) and use the CRB as a performance benchmark. Simulation results verify that the proposed algorithm can realize accurate parameter estimation and localization compared to the existing algorithms. The influence of the sampling numbers on the estimation performance is also investigated. Simulation results reveal that even in the case of small sampling numbers, the proposed algorithm still has excellent performance.