Location-driven beamforming for massive multi-user MIMO systems

Using the existing positioning technology can easily obtain high-precision positioning information, which can save resources and reduce complexity when used in the communication field. In this paper, we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system. Specifically, we combine an analog outer beamformer with a digital inner beamformer. An outer beamformer can be selected from a codebook formed by antenna steering vectors, and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices (QR) decomposition is applied to cancel interuser interference. Then, we propose a low-complexity user selection algorithm using location information in this paper. We first derive the geometric angle between channel matrices, which represent the correlation between users. Furthermore, we derive the asymptotic signal to interference-plus-noise ratio (SINR) of the system in the context of two-stage beamforming using random matrix theory (RMT), taking into account inter-channel correlations and energies. Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.