Abstract
This work presents two-dimensional (2D) direction-of-arrival (DOA) estimation for massive multiple-input multiple-output (MIMO) system using a low complexity algorithm. The proposed algorithm utilizes propagator method (PM) for the initial estimates of factor matrices to increase the convergence rate of canonical polyadic (CP) decomposition also known as parallel factor (PARAFAC) analysis. To represent massive MIMO system, uniform rectangular array (URA) has been selected. The proposed algorithm does not involve eigenvalue decomposition (EVD) of covariance matrix, and additional pair-matching methods for azimuth and elevation angles. Furthermore, with fast convergence trilinear decomposition approach the computational complexity reduces significantly. The proposed method can give the estimation performance close to that of PARAFAC with low computational burden and outperforms ESPRIT and PM methods. Numerical simulations show the efficacy and validity of proposed algorithm (PM-PARAFAC) for massive MIMO systems.
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