An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems

• Published in: IEEE journal of selected topics in signal processing 2014-10, Vol.8 (5), p.996-1011
• Main Authors: Hu, Anzhong, Lv, Tiejun, Gao, Hui, Zhang, Zhang, Yang, Shaoshi
• Format: Article
• Language: English
• Subjects: Angular spread; Antennas; Azimuth; Complexity; Computation; Covariance matrices; direction-of-arrival (DOA); Direction-of-arrival estimation; Estimating; Estimation; Estimators; large-scale/massive multiple-input multiple-output (LS-MIMO/massive MIMO); Localization; Manifolds; Mathematical models; MIMO; Position (location); Searching; two-dimensional (2-D) localization; very large arrays
• ISSN: 1932-4553; 1941-0484
• DOI: 10.1109/JSTSP.2014.2313409

In this paper, an approach of estimating signal parameters via rotational invariance technique (ESPRIT) is proposed for two-dimensional (2-D) localization of incoherently distributed (ID) sources in large-scale/massive multiple-input multiple-output (MIMO) systems. The traditional ESPRIT-based methods are valid only for one-dimensional (1-D) localization of the ID sources. By contrast, in the proposed approach the signal subspace is constructed for estimating the nominal azimuth and elevation direction-of-arrivals and the angular spreads. The proposed estimator enjoys closed-form expressions and hence it bypasses the searching over the entire feasible field. Therefore, it imposes significantly lower computational complexity than the conventional 2-D estimation approaches. Our analysis shows that the estimation performance of the proposed approach improves when the large-scale/massive MIMO systems are employed. The approximate Cramér-Rao bound of the proposed estimator for the 2-D localization is also derived. Numerical results demonstrate that albeit the proposed estimation method is comparable with the traditional 2-D estimators in terms of performance, it benefits from a remarkably lower computational complexity.