Efficient Angle Estimation for MIMO Systems via Redundancy Reduction Representation
Yu Zhang (Nanjing University of Aeronautics and Astronautics)
Yue Wang (George Mason University)
Zhi Tian (George Mason University)
Geert J.T. Leus (TU Delft - Signal Processing Systems)
Gong Zhang (Nanjing University of Aeronautics and Astronautics)
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Abstract
This paper proposes an efficient direction of departure (DOD) and direction of arrival (DOA) estimation method for multi-input multi-output (MIMO) systems. For uncorrelated scenarios, the redundancy of the covariance matrix is first exploited by establishing its concise representation through redundancy reduction, which transforms the original large-size covariance matrix into a smaller-size matrix without loss of useful angle information. Then, the resulting transformed matrix, which retains a salient structure, permits efficient two-dimensional (2D) angle estimators working on a reduced-size problem for DOD and DOA estimation. Compared with conventional subspace-based methods, the proposed method incorporating an appropriate 2D angle estimator is more computationally efficient and can achieve higher estimation accuracy for small numbers of snapshots and low signal-to-noise ratios, which are verified by simulation results.