A Priority-Aware AI-Generated Content Resource Allocation Method for Multi-UAV Aided Metaverse
With the advancement of large model technologies, AI -generated content is gradually emerging as a mainstream method for content creation. The metaverse, as a key application scenario for the next-generation communication technologies, heavily depends on advanced content generation technologies. Nevertheless, the diverse types of metaverse applications and their stringent real-time requirements constrain the full potential of AIGC technologies within this environment. In order to tackle with this problem, we construct a priority-aware multi-UAV aided metaverse system and formulate it as a Markov decision process (MDP). We propose a diffusion-based reinforcement learning algorithm to solve the resource allocation problem and demonstrate its superiority through enough comparison and ablation experiments.
Authors
- Chunxiao Jiang (ORCID: https://orcid.org/0000-0002-3703-121X)
- Jianrui Chen (ORCID: https://orcid.org/0000-0003-3189-4222)
- Zheng Zhang (ORCID: https://orcid.org/0009-0002-5689-4253)
- Zhengru Fang
- Zhu Han
- Jingjing Wang (ORCID: https://orcid.org/0000-0003-3170-8952)
Institutions
- City University of Hong Kong (HK)
- University of Houston (US)
- Beihang University (CN)
- Tsinghua University (CN)
Publication Details
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1109/wcnc61545.2025.10978443
- Citations
- 1
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21