UE Radio Link Failure Prediction for Proactive Handover
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing handover technologies in wireless communication systems, particularly in densely deployed microcell environments with high UE mobility, suffer from issues such as handover failures, radio link failures (RLF), and throughput losses due to reactive approaches based on measurement events and reporting, leading to significant user inconvenience.
Innovation Solution
A method and device for predicting RLF using an AI/ML-based prediction model for signal measurement, where a UE or base station receives configuration information to input signal measurement results, enabling proactive RLF prediction and resource allocation for seamless communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If reactive handover technologies based on measurement events and reporting are used, then handover procedures can be triggered based on actual conditions, but handover failures and radio link failures occur more frequently in densely deployed microcells with high UE mobility
Solution Approach 1:
The patent applies preliminary action by using AI/ML prediction models to forecast RLF occurrence before it actually happens. The system continuously monitors signal measurements and inputs them into the prediction model to anticipate future RLF conditions, enabling proactive handover preparation and execution before the reactive measurement-based approach can respond, thereby preventing handover failures in high-mobility microcell environments
2Loss of time
If typical reactive handover procedures are implemented, then the system can respond to current signal conditions, but service interruptions and throughput losses increase due to the response delay
Solution Approach 1:
The AI/ML-based prediction model performs preliminary analysis of signal measurements to forecast RLF occurrence before it actually occurs. This allows the system to initiate handover procedures in advance, eliminating the delay inherent in reactive approaches where handover is triggered only after RLF has already occurred or measurement events are detected, thereby preventing throughput losses and service interruptions
3Measurement precision
If measurement events and reporting are used for handover determination, then handover decisions can be based on actual signal conditions, but unexpected handover failures occur causing user inconvenience
Solution Approach 1:
The system implements feedback by continuously monitoring signal measurements and feeding them into the AI/ML prediction model. The model processes these measurements to predict future RLF conditions, providing early warning feedback that enables proactive handover preparation. This feedback loop operates independently of traditional measurement events, enhancing handover robustness by anticipating failures before they occur based on patterns learned from historical data
Data Source
AI summary
Provided are a method and device for proactively predicting a radio link failure (RLF) of a UE. The method may include receiving configuration information for RLF prediction from a base station, performing signal measurement of a serving cell based on the configuration information, and predicting an RLF occurrence using an RLF output result output from a preconfigured prediction model by inputting a signal measurement result to the prediction model.