Game-Theoretic Power Allocation for Network Slicing in NOMA-Based 5G Networks: A Stackelberg Approach

This paper investigates power allocation optimization in 5G networks utilizing Non-Orthogonal Multiple Access (NOMA) and network slicing, with a focus on Ultra-Reliable Low-Latency Communication (URLLC) and Enhanced Mobile Broadband (eMBB) slices. Addressing the challenge of reducing latency in the URLLC slice while boosting throughput in the eMBB slice, a Stackelberg game-theoretic approach is applied to model the hierarchical interactions between network slices. The base stations (BS) in the URLLC and eMBB slices act as leaders, and the users as followers. The study's findings reveal that the proposed method effectively minimizes latency in the URLLC slice and improves throughput in the eMBB slice, highlighting the efficacy of the Stackelberg algorithm in managing power distribution to meet diverse network slice requirements.