Mobility Prediction Model Reconfiguration for 5G Handover Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mobility prediction models in communications systems, particularly in 5G networks, face challenges due to varying radio environments and communication latency, leading to inaccurate predictions and sub-optimal network and UE actions.
Innovation Solution
The proposed solution involves a method where User Equipment (UE) performs mobility predictions using a configured Mobility Prediction Model (MPM) and reports the predictions to a network node, which determines if MPM re-configuration is needed, allowing for dynamic updates and improved accuracy by adjusting the prediction models based on current error levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mobility prediction models are used in 5G networks, then handover performance and network optimization are improved, but prediction accuracy deteriorates due to varying radio environments and communication latency
Solution Approach 1:
The patent implements a feedback mechanism where the UE reports MPM performance information (prediction accuracy metrics) back to the network node. The network node uses this feedback to dynamically adjust and reconfigure the MPM parameters, creating a closed-loop system that continuously improves prediction accuracy by learning from actual performance data.
Solution Approach 2:
The patent makes the MPM dynamic by allowing reconfiguration of its parameters based on current network conditions and UE behavior patterns. The model transitions from a static prediction structure to a dynamic one that adapts its parameters in real-time, enabling it to handle varying radio environments and maintain high prediction accuracy.
2Measurement precision
If MPM re-configuration is implemented, then prediction accuracy is improved, but system complexity increases due to additional reporting and processing requirements
Solution Approach 1:
The patent applies partial action by selectively reconfiguring only the MPM parameters that need updating, rather than replacing the entire model. The network node determines which specific parameters require adjustment based on the feedback information, applying changes only where necessary to maintain accuracy while minimizing processing overhead.
Solution Approach 2:
The UE performs self-monitoring of MPM performance and autonomously generates reports about prediction accuracy to the network node. This self-service approach reduces the need for complex network-side monitoring systems, as the UE independently tracks and communicates its own performance metrics.
3Measurement precision
If real-time MPM updates are performed, then prediction accuracy is maintained, but communication overhead increases due to frequent reporting requirements
Solution Approach 1:
The patent implements periodic action by having the UE report MPM performance information at scheduled intervals or when specific triggering conditions are met, rather than continuously reporting. This periodic reporting mechanism maintains prediction accuracy through regular updates while significantly reducing communication overhead compared to continuous monitoring and reporting.
Solution Approach 2:
The patent uses parameter changes in the reporting mechanism by adjusting the frequency and granularity of reports based on current network conditions. The network node can modify reporting parameters (such as report intervals or threshold values) to optimize the balance between maintaining accurate predictions and minimizing communication overhead.
Data Source
AI summary
The present disclosure relates to a method performed by a UE (105) for handling MPM re-configuration in a communications system (100). The UE (105) is configured with a first MPM. The UE (105) performs mobility predictions using the first MPM. The CE (105) provides a report from the mobility predictions to a network node (101). The UE (105) obtains MPM re-configuration information from the network node (101). The UE (105) preforms MPM re-configuration according to the obtained MPM-re-configuration information.