Diffusion Model-based Metaverse Rendering in UAV-Enabled Edge Networks With Dual Connectivity

Metaverse is an immersive, seamless, interactive, comprehensive virtual world, as well as a replication, extension, and transcendence of the real world. Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) is becoming a key technology for ubiquitous Metaverse services. To enhance network resource utilization, we introduce dual connectivity (DC) technologies in UAV-enabled MEC, which increases the time complexity associated with resource management. Considering the specific features of DC communication channels, we propose a UAV-assisted Metaverse rendering problem to enhance the Metaverse service experience and reduce the energy cost of edge devices. To solve the rendering problem with low complexity, we propose a diffusion model-based Metaverse rendering algorithm, where a novel diffusion model is used to generate integer rendering decisions with the aid of the gradient provided by the model-based Metaverse rendering problem. Moreover, with the given rendering decisions, the communication and computation resource allocation results are derived by the model-based optimization method. Finally, we conduct extensive simulation experiments based on real-world datasets. Comprehensive simulation results demonstrate that the diffusion model-based Metaverse rendering algorithm can reduce the Metaverse frame rendering time and improve user experience.