Energy Efficiency and Connectivity Maximization for Massive Machine Type Communication in Multi-Cell NOMA

We propose a resource allocation and scheduling framework for future ultra-massive machine-type communication (umMTC) in 6G using Non-Orthogonal Multiple Access (NOMA) to maximize energy efficiency (EE). Within this framework, we consider the practical limitations of umMTC, such as limited radio resources and stringent device power requirements. The framework ensures minimal interference between users and addresses the challenges of accommodating dense deployments while ensuring reliable connectivity. To address the massive connectivity problem, we formulated a constrained optimization problem for energy efficiency and connectivity to define the scheduling research problem. However, the resource allocation problem is typically infeasible due to non-convexity and the use of binary variables. Therefore, our objective is to maximize energy efficiency and connectivity by proposing an energy-efficient resource scheduling and power allocation algorithm for umMTC based on NOMA (EERS-MTCN). The simulation results show that the proposed scheme improves energy efficiency by 160% and 55% (for a high user density of 400 users/m²) compared to the NOMA-based reference schemes.