QoE Analysis and Resource Allocation for Wireless Metaverse Services

The seamless and ubiquitous wireless access is crucial to the immersive experiences in the metaverse. Considering the limited communication and computing resources, how to provide metaverse services with high Quality of Experience (QoE) for users is still challenging. In this paper, an innovative QoE model for metaverse services based on the virtual distance and network effect is proposed. Especially, we introduce a novel metric called “meta-distance” to measure virtual distance in the metaverse, which jointly considers the service delay and social distance among metaverse users. To solve the QoE utility maximization problem, we propose a Joint Resource Allocation and Metaverse service Selection (JRAMS) scheme, which is composed of a two-step mechanism. In the first step, referred to as the inner loop of JRAMS, a one-to-many matching game with externalities is used to match base stations and metaverse users with Non-Orthogonal Multiple Access (NOMA) based subchannel allocation. In the second step, referred to as the outer loop of JRAMS, a hedonic coalition formation game is used to solve the metaverse service selection problem. After finite iterations, JRAMS can converge to a stable solution. The simulation results show that compared with baselines, the average QoE utility of JRAMS can be significantly improved.