Two-Stage Power Allocation for IRS-Assisted Downlink NOMA: Intra-Group Optimization and Inter-Group Allocation

Non-Orthogonal Multiple Access (NOMA) has emerged as a key enabler for massive connectivity in next-generation networks, while Intelligent Reflecting Surfaces (IRS) provide a transformative approach to enhancing spectral efficiency by reconfiguring the wireless propagation environment. However, integrating IRS with downlink NOMA presents significant challenges in power allocation, user grouping, and interference management, with existing methods often struggling to balance power efficiency, quality-of-service (QoS) guarantees, and computational scalability. This paper investigates a two-stage power allocation framework for IRS-assisted downlink NOMA. The first stage performs intra-group optimization, jointly adjusting user-level power allocation and IRS phase shifts to minimize power consumption while meeting QoS requirements based on an iterative optimization procedure. The second stage optimizes inter-group, allocating power across user groups to maximize the number of served users based on a sequential fixing programming procedure. A detailed complexity analysis demonstrates the computational efficiency of the framework, enabling real-time deployment in dynamic networks. The simulation results confirm that the proposed approach achieves superior sum rate performance while minimizing total power consumption and maintaining QoS guarantees.