Optimizing Connectivity and Scheduling of Near/Far Field Users in Massive MIMO NOMA System

It is envisioned that the next generations of wireless communication environment will be characterized with dense traffic demand due to the prediction that there will be large numbers of active users. Hence, it is important to find a solution to deal with such dense numbers of users. This paper investigates optimizing the connectivity and users scheduling to improve the performance of near and far field users in a downlink, multiuser, massive MIMO-NOMA system. For the considered system model, combining NOMA side by side with massive MIMO offers a great opportunity to exploit the available radio resources and boost the overall system efficiency. The paper proposes separate clustering of near field users and far field users. It also proposes using a beamforming scheme to separately serve the users within each cluster. However, NOMA is proposed to be applied among all users to boost resource sharing. In particular, a cognitive-NOMA beamforming scheme and NOMA themed beamforming are proposed to serve the users within each cluster, and they are compared against random beamforming from literature. Simulation results show that both of the proposed beamforming schemes proved their superiority as compared to random beamforming. Several scheduling techniques were also considered in this paper to examine possible solutions for boosting the system performance considered, namely, priority, joint, dynamic, and fairness-based scheduling techniques for both near field and far field users. The paper also proposes a suboptimal, fairness aiming and gradual allocation approach for allocating the transmission power among the users. The results show that user-clustering offers better connectivity and scheduling performance than the case where no clustering is applied.