Joint Subchannel and User Scheduling for Wireless Metaverse Services: A Genetic Algorithm-Based Approach

The metaverse, offering immersive and interactive experiences, has become a key focus resently. In this letter, we investigate a metaverse wireless communication system incorporating Non-Orthogonal Multiple Access (NOMA). To strike an effective balance between user Quality of Experience (QoE) and system cost, we propose a comprehensive algorithmic framework. Specifically, the problem is decomposed into two subproblems: subchannel allocation and user scheduling. For these, we design a NOMA-based Subchannel Allocation algorithm (NSA) and a Genetic Algorithm-based Joint User and Subchannel Allocation scheme (GA-JUSA), which are executed iteratively to enhance overall performance. Experimental results show that the proposed approach achieves up to a 22.98% improvement over existing methods, highlighting its potential for future applications.