AI-assisted Improved Service Provisioning for Low-latency XR over 5G NR
This work addresses the problem of service provisioning for low-latency XR applications over 5G/6G networks, which is crucial for transforming human interactions, but it appears incremental as it builds on existing AI and prediction methods.
The paper tackles the challenge of ensuring low latency, high data rate, and reliability for Extended Reality (XR) services over 5G networks by proposing an AI-assisted service provisioning scheme that uses predicted frames to increase the network delay budget, resulting in a multi-fold increase in supported XR users as validated by simulations.
Extended Reality (XR) is one of the most important 5G/6G media applications that will fundamentally transform human interactions. However, ensuring low latency, high data rate, and reliability to support XR services poses significant challenges. This letter presents a novel AI-assisted service provisioning scheme that leverages predicted frames for processing rather than relying solely on actual frames. This method virtually increases the network delay budget and consequently improves service provisioning, albeit at the expense of minor prediction errors. The proposed scheme is validated by extensive simulations demonstrating a multi-fold increase in supported XR users and also provides crucial network design insights.