DOA and Polarization Estimation for Polarized Massive MIMO Systems in an Impulsive Noise Environment

To address the limitations of existing joint estimation methods for the direction of arrival (DOA) and polarization information, which are computationally intensive and vulnerable to impulsive noise, this paper proposes an estimation method for the joint estimation of DOA and polarization information in polarized massive multiple-input-multiple-output (MIMO) systems operating in the presence of impulsive noise. The method is based on maximum likelihood (ML) estimation and derives the Cramér–Rao bound (CRB) in impulsive noise environments. An infinite norm normalization covariance is employed to mitigate the effects of impulsive noise, and a quantum Giza pyramid construction algorithm (QGPCA) is devised to swiftly resolve the objective function without incurring quantization error, thus enabling the identification of the globally optimal solution for the estimation method. The results of the simulations demonstrate that the proposed method achieves higher estimation accuracy and robustness in the presence of small snapshots and a low generalized signal-to-noise ratio (GSNR).