XR Traffic Resource Allocation in 5G Networks
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Solution Overview
Problem
Existing network resource allocation solutions do not effectively account for extended reality (XR) network traffic, leading to suboptimal user experiences and performance losses in XR applications over 5G or 6G networks due to latency sensitivity and data intensity.
Innovation Solution
A system that determines traffic characteristics of XR network traffic using machine learning models and applies dynamic or semi-static resource allocation grants to optimize resource allocation in 5G or 6G radio access networks, prioritizing XR traffic based on packet size distribution and inter-arrival time models to ensure optimal performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing network resource allocation solutions are used, then general network traffic is handled, but XR-specific latency and performance requirements are not met
Solution Approach 1:
The patent applies local quality by implementing XR-specific resource allocation rules that differ from general traffic handling. The network device identifies XR traffic packets and applies dedicated resource allocation configurations (such as prioritized scheduling, guaranteed bandwidth, or low-latency queues) specifically to these packets, while other traffic continues to use standard allocation mechanisms. This ensures that XR traffic receives the specialized treatment needed to meet its strict QoS requirements without affecting other network traffic.
Solution Approach 2:
The patent implements dynamics by enabling the network device to dynamically identify XR traffic packets in real-time and adapt resource allocation on-the-fly. The system continuously monitors incoming packets, identifies those belonging to XR applications, and adjusts resource allocation parameters dynamically based on current network conditions and XR-specific requirements. This allows the network to flexibly respond to varying XR traffic patterns and maintain optimal performance.
2Productivity
If network resource allocation is optimized for general traffic, then overall network throughput is maintained, but XR application latency increases
Solution Approach 1:
The patent applies segmentation by dividing network traffic into distinct categories: XR traffic packets and non-XR traffic packets. The network device implements separate resource allocation mechanisms for each category, with XR packets receiving prioritized handling through dedicated queues, reserved bandwidth, or expedited scheduling. This segmentation ensures that XR traffic does not compete with general traffic for network resources, thereby reducing latency while maintaining overall network throughput by allowing non-XR traffic to continue using standard allocation.
3Reliability
If dynamic resource allocation is implemented for XR traffic, then QoS requirements are met, but network complexity increases
Solution Approach 1:
The patent introduces an intermediary component in the form of an XR traffic identifier or classification mechanism that sits between the general packet processing pipeline and the specialized XR resource allocation rules. This intermediary identifies XR packets using predefined criteria (such as protocol signatures, port numbers, or application-layer indicators) and routes them to the appropriate QoS handling logic. By using this intermediary layer, the system achieves complex XR-specific QoS compliance without requiring fundamental restructuring of the entire network allocation infrastructure, thus managing complexity effectively.
Data Source
AI summary
Resource allocation of network traffic comprising extended reality network traffic (e.g., using a computerized tool) is enabled. For example, a method can comprise: determining, by network equipment comprising a processor, whether network traffic via a radio access network comprises extended reality network traffic; in response to a determination that the network traffic comprises the extended reality network traffic, determining, by the network equipment, a traffic characteristic of the extended reality network traffic; based on the traffic characteristic, determining, by the network equipment, a resource allocation for the network traffic; and in response to determining the resource allocation for the network traffic, applying, by the network equipment, the resource allocation to a network node of the radio access network.