Application-Driven Offloading of XR Mission Critical via Integrated TN/NTN

Abstract

The emergence of eXtended Reality (XR) technologies is revolutionizing Mission Critical (MC) operations by enhancing situational awareness and decision-making. However, the high computational demands of XR MC applications, coupled with the limited capabilities of battery-powered wearable XR devices worn, e.g., by first responders, necessitate offloading strategies to more processing-powerful network nodes. Traditional terrestrial networks, while supporting XR MC services, may not be reliable in all scenarios, especially during emergencies or in remote areas. To address this, the integration of Non-Terrestrial Networks (NTNs) with Terrestrial Networks (TNs) offers various options to place and run in-network computing tasks, e.g., Low Earth Orbit (LEO) satellites and Unmanned Aerial Vehicles (UAVs). The potential of these offloading options for XR MC services has not yet been fully explored. In this work, we close this gap and analyze the performance of application-driven offloading of computational tasks of XR MC services at different locations in the integrated TN/NTN environment. Through system-level simulations, we assess the end-to-end latency cost under different traffic loads at the various system layers and analyze the energy consumption of XR device, identifying practical insights for system designers. For a small number of requests, offloading is more effective than local computing, improving performance by up to 93%, whereas, for a high number of requests, local computing is preferred but constrained by battery limitations.