Abstract
With the quick advancement of wireless communication networks, the need for massive multiple-input-multiple-output (MIMO) to offer adequate network capacity has turned out to be apparent. As a portion of array signal processing, direction-of-arrival (DOA) estimation is of indispensable significance to acquire directional data of sources and to empower the 3D beamforming. In this paper, the performance of DOA estimation for massive MIMO systems is analyzed and compared using a low-complexity algorithm. To be exact, the 2D Fourier domain line search (FDLS) MUSIC algorithm is studied to mutually estimate elevation and azimuth angle, and arbitrary array geometry is utilized to represent massive MIMO systems. To avoid the computational burden in estimating the data covariance matrix and its eigenvalue decomposition (EVD) due to the large-scale sensors involved in massive MIMO systems, the reduced-dimension data matrix is applied on the signals received by the array. The performance is examined and contrasted with the 2D MUSIC algorithm for different types of antenna configuration. Finally, the array resolution is selected to investigate the performance of elevation and azimuth estimation. The effectiveness and advantage of the proposed technique have been proven by detailed simulations for different types of MIMO array configuration.
Highlights
The use of multiple antennas at the two finishes of wireless links is the consequence of the natural progression of more than four decades of advancement of adaptive antenna technology
There are several signal processing functions performed in MIMO systems, among which 3D beamforming for link reliability enhancement has gotten impressive consideration
The performance of DOA estimation for massive MIMO systems is assessed in [13] using a lowcomplexity algorithm; good performance was achieved, but this method is unsubstantial for arbitrary array structure
Summary
The use of multiple antennas at the two finishes of wireless links is the consequence of the natural progression of more than four decades of advancement of adaptive antenna technology. Late advances have shown that multiple-inputmultiple-output (MIMO) wireless systems can accomplish great increments in the overall system performance Such frameworks are expected for the development of new generations of mobile radio systems for future wireless communication standards and applications. The performance of DOA estimation for massive MIMO systems is assessed in [13] using a lowcomplexity algorithm; good performance was achieved, but this method is unsubstantial for arbitrary array structure. Development of low-complexity DOA estimation algorithms for massive MIMO systems in arbitrary array configuration becomes extremely necessary for a practical implementation perspective. 2D Fourier domain line search MUSIC (FDLSM) is introduced to jointly estimate elevation and azimuth information for massive MIMO systems. This paper fundamentally concentrates on a lowcomplexity 2D DOA estimation using the 2D FDLSM algorithm with a reduced-dimension transformation in massive MIMO systems.
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