Successive Location Information Assisted User Selection for Massive MIMO Systems

Massive multi-input multi-output (Massive MIMO) technology is considered as one of the most breakthrough technologies in the fifth generation wireless communication networks. However, with the rapid growth of the number of users and antennas, traditional signal processing techniques will produce computational complexity that the system cannot burden. At the same time, the number of users is increasing, and increased interference between users can lead to serious system performance losses. In response to many challenges, a two-stage scheme Successive Location Information Assisted User Selection (SLI-AUS) scheme is proposed in this paper. Specifically, we first propose constrained spatial density clustering (DBCluC) for all candidate users using successive location information. According to the clustering results, the user class with the worst channel energy was screened out. In the second stage, based on the location information, the geometric Angle which can represent the correlation between channels is calculated, and the progressive SINR which represents the channel energy is adopted as the criteria for user selection. The simulation results show that compared with the original scheme, the proposed scheme has lower computational complexity while ensuring the system performance.