Adaptive Mobility Measurement Reporting for XR Services
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Solution Overview
Problem
Conventional measurement reporting techniques for mobility operations in 5G/NR networks are not suitable for User Equipment (UE) using Extended Reality (XR) services, which require high throughput and low latency, leading to inadequate mobility performance and service continuity.
Innovation Solution
The implementation of specific methods for User Equipment (UE) to determine traffic types and select corresponding measurement configurations based on parameters such as data rate, traffic patterns, and quality-of-service metrics, allowing for adaptive measurement reporting and improved handover procedures in 5G networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional measurement reporting techniques are used, then device complexity is reduced, but mobility performance and service continuity deteriorate for XR services
Solution Approach 1:
The patent implements dynamic measurement reporting by adjusting reporting parameters based on traffic type identification. The UE determines whether traffic is XR or non-XR and applies different measurement configurations accordingly, making the system adaptive rather than static. This resolves the contradiction by dynamically optimizing for XR services when needed while maintaining simplicity for conventional services.
Solution Approach 2:
The patent changes measurement reporting parameters based on traffic type. Different measurement configurations (with different thresholds, periodicities, and triggers) are applied depending on whether the traffic is identified as XR or non-XR. This parameter adaptation enables reliable service continuity for XR while avoiding unnecessary complexity for other services.
2Speed
If measurement reporting is optimized for XR services, then mobility performance improves, but device complexity increases
Solution Approach 1:
The patent segments measurement configurations into distinct sets for different traffic types. Instead of one complex configuration handling all cases, separate measurement configurations are defined for XR and non-XR traffic. The UE selects the appropriate segment based on traffic type identification, achieving fast handovers for XR without universally increasing complexity.
Solution Approach 2:
The UE autonomously determines traffic type and selects appropriate measurement configurations without requiring complex network control for each decision. The device serves itself by internally managing the selection between different measurement regimes based on identified traffic patterns, reducing overall system complexity while maintaining fast handover capability.
3Reliability
If conventional measurement configurations are used, then ease of operation is maintained, but QoS degradation occurs under increased traffic loads
Solution Approach 1:
The system implements feedback through traffic type identification and adaptive measurement configuration selection. The UE monitors traffic characteristics, identifies XR traffic types, and adjusts measurement reporting accordingly. This feedback loop ensures QoS is maintained under increased loads by activating optimized configurations when XR traffic is detected, without requiring manual intervention.
4Duration of action of stationary object
If traffic-type-specific measurement configurations are implemented, then service continuity improves, but information processing requirements increase
Solution Approach 1:
The patent applies partial action by implementing traffic type-specific measurement configurations only when needed. The UE identifies XR traffic and applies enhanced measurement procedures selectively rather than continuously. This reduces unnecessary processing energy consumption for non-XR traffic while maintaining service continuity for XR services when required.
Data Source
AI summary
Embodiments include methods for a user equipment (UE) configured to communicate data corresponding to multiple traffic types with a network node of a wireless network. Such methods include determining a traffic type associated with data communicated between the UE and the network node and selecting a measurement configuration based on the determined traffic type. The selected measurement configuration includes values, of at least one parameter, that are associated with the determined traffic type. Such methods also include performing one or more measurements on downlink (DL) signals from the wireless network according to the selected measurement configuration. Other embodiments include complementary methods for a network node, as well as UEs and network nodes configured to perform such methods.