Density-based user clustering in downlink NOMA systems

Non-orthogonal multiple access (NOMA) technology, which can effectively improve the bandwidth utilization, is one of the key technologies in the next-generation wireless communication systems. In the downlink multiple antenna NOMA systems, user clustering is one of the problems that must be solved. In this paper, we focus on the user clustering that maximizes the system sum rate. First, a user clustering method based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed for static user scenarios. Then an improved low-complexity dynamic clustering method is further developed for dynamic user scenarios. Simulation results show that compared with existing clustering methods, the DBSCAN-based method has better clustering performance in complex static user scenarios, and the proposed dynamic clustering method performs close to completely re-executing the DBSCAN-based method but with lower complexity.