In this paper, an approach of estimating signal parameters via rotationalinvariance technique (ESPRIT) is proposed for two-dimensional (2-D)localization of incoherently distributed (ID) sources in large-scale/massivemultiple-input multiple-output (MIMO) systems. The traditional ESPRIT-basedmethods are valid only for one-dimensional (1-D) localization of the IDsources. By contrast, in the proposed approach the signal subspace isconstructed for estimating the nominal azimuth and elevationdirection-of-arrivals and the angular spreads. The proposed estimator enjoysclosed-form expressions and hence it bypasses the searching over the entirefeasible field. Therefore, it imposes significantly lower computationalcomplexity than the conventional 2-D estimation approaches. Our analysis showsthat the estimation performance of the proposed approach improves when thelarge-scale/massive MIMO systems are employed. The approximate Cram\'{e}r-Raobound of the proposed estimator for the 2-D localization is also derived.Numerical results demonstrate that albeit the proposed estimation method iscomparable with the traditional 2-D estimators in terms of performance, itbenefits from a remarkably lower computational complexity.
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