A Beamspace-Based DOA Estimation Algorithm for 2D Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is significantly promising in the fifth generation (5G) mobile communication systems. The direction-of-arrival (DOA) is particularly crucial for base stations (BSs) to perform beamforming in massive MIMO systems. Due to being equipped with hundreds of antennas at the BSs, the traditional DOA estimation algorithms such as MUSIC and ESPRIT algorithm have extremely high computational complexity and are not suitable for realistic massive MIMO systems. In this paper, a novel two-dimensional beamspace-based Propagator Method (2D BPM) algorithm with a uniform rectangular array (URA) for DOA estimation is proposed. We firstly utilize beamspace transform matrix to convert the steering matrix of the array space into the beamspace. And then DOA estimation is performed based on the PM algorithm. Therefore, the proposed algorithm can significantly decrease the dimension of the received signal vector and avoid eigenvalue decomposition (EVD) on a high-dimensional covariance matrix compared with subspace algorithms. The 2D BPM algorithm achieves better performance and lower computational complexity. Numerical simulation results clearly demonstrate that the proposed approach has not only a high DOA estimation precision but also a lower computational complexity in massive MIMO systems.