Jointly optimizing user clustering, power management, and wireless channel allocation for NOMA-based Internet of Things

In order to accommodate the large number of Internet of Things (IoT) connections in mobile networks, Non-Orthogonal Multiple Access (NOMA) has been applied as the resource sharing mechanism in mobile access networks to improve the spectrum efficiency. The NOMA-based resource management for uplink communications comprises two problems, i.e., user clustering and power & wireless channel allocation. User clustering refers to assigning users in terms of IoT devices to different clusters (where users in the same cluster are sharing the wireless channels to upload their data), and power & wireless channel allocation is to optimize the transmission power of the users and the number of wireless channels allocated to the users in a cluster. The two problems are coupled together, thus making it difficult to solve the NOMA-based resource management problem. In this paper, we propose a QoS-aWarE resourcE managemenT (SWEET) for NOMA algorithm to jointly optimize the user clustering, power management, and wireless channel allocation such that the number of wireless channels is minimized and the data rate requirements of the users can be satisfied. The performance of SWEET is validated via extensive simulations.