Enabling Generative AI based Multi-sensory XR Applications with Mobile Edge Computing

With the rapid development of XR devices, holographic applications are expanding across various domains. However, it is a consensus that capturing and transmitting real-time holographic content still requires significant bandwidth. Even with the enhanced wireless capabilities of mobile systems, they still fall short of meeting the bandwidth and latency demands required for near-Gigabit per second interactive application scenarios. This paper proposes a network architecture that leverages MEC to address these challenges with the assistant of Generative AI. In this framework, the MEC server can leverage the power of the generative AI model to generate holographic objects with the input of user semantic commands, instead of requiring end-users to capture and transmit large raw holographic data. This approach significantly reduces uplink bandwidth requirements while enabling efficient real-time content generation. To validate this approach, we design an interactive and multisensory operational training scenario relying solely on semantic uplink transmissions from the end-users. The preliminary results based on the testbed implemented highlight the feasibility of deploying diverse holographic applications in wireless environments.