Journal
SIGNAL PROCESSING
Volume 176, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.sigpro.2020.107702
Keywords
Massive MIMO; DOA estimation; Adaptive estimation; Wideband signal; Subspace
Categories
Funding
- National Natural Science Foundation of China [61761033, 61671105]
- Natural Science Foundation of Inner Mongolia Autonomous Region of China [2019MS06033]
- Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region [NJYT-20-A11]
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For massive multiple-input multiple-output (MIMO) communication systems, it is a major challenge to develop direction-of-arrival (DOA) estimation algorithm with low complexity and high accuracy for wide band signals. We propose a low-complexity adaptive multistage Wiener filter (MSWF)-based two-sided correlation transformation (AM-TCT) algorithm for wideband DOA estimation of two-dimensional (2D) massive MIMO systems. Unlike conventional TCT algorithms, the proposed AM-TCT algorithm uses the signal subspace that is obtained by forward recursion of the MSWF to construct the focusing matrix, which can reduce the computational complexity. To further reduce the computational complexity, the eigenvalue decomposition (EVD) of the covariance matrix is also replaced by the MSWF. Furthermore, to improve the precision, the Minimum Description Length (MDL) criterion uses the stage of MSWF to adaptively select the appropriate dimension of the noise subspace, and the backward recursion of the MSWF is employed to accurately estimate the noise subspace. Theoretical analysis demonstrates the complexity superiority of the proposed AM-TCT algorithm. Simulation results indicate that the proposed AM-TCT algorithm can effectively estimate the angle of wideband sources in massive MIMO systems and outperform some existing methods. (c) 2020 Elsevier B.V. All rights reserved.
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