SCG Handover Failure Categorization in MR-DC
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Solution Overview
Problem
Current Multi-Radio Dual Connectivity (MR-DC) systems lack a method to categorize Secondary Cell Group (SCG) handover failures, specifically too late, too early, or wrong cell handover, which hinders fine-tuning of handover parameters to reduce failure rates.
Innovation Solution
A system and method that categorize SCG handover failures by analyzing Radio Link Failure (RLF) messages, including New Radio measurement results, to determine whether the failure was too early, too late, or wrong cell handover, allowing for appropriate parameter adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SCG handover is implemented in MR-DC systems, then network mobility and connectivity are improved, but handover failure rate increases due to lack of failure categorization capability
Solution Approach 1:
The patent segments handover failures into distinct categories (too early, too late, wrong cell) based on measurement results and failure timing. This segmentation enables targeted parameter adjustments for each failure type, improving handover success rates while maintaining manageable system complexity through structured failure analysis.
Solution Approach 2:
The patent implements a feedback mechanism where the network node receives failure reports from UEs containing measurement results, analyzes these reports to categorize failures, and uses this information to fine-tune handover parameters. This closed-loop feedback system continuously improves handover reliability based on actual failure patterns observed in the network.
2Measurement precision
If detailed analysis of RLF messages and measurement results is performed to categorize failures, then handover parameter fine-tuning capability is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary actions by having UEs collect and report measurement results (RSRP, RSRQ, SINR) before handover failure occurs. These pre-collected measurements are included in failure reports, enabling the network to categorize failures without requiring complex post-failure analysis, thus reducing processing complexity while maintaining high measurement precision.
Solution Approach 2:
The patent uses copies of measurement data and failure information reported by UEs to perform failure categorization. Instead of requiring the network to directly measure and analyze all parameters, it processes copied information from UE reports, significantly reducing processing complexity while maintaining analysis precision through structured data formats.
3Adaptability or versatility
If SCG handover failure categorization is implemented, then ability to fine-tune handover parameters is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent applies local quality by implementing failure categorization and parameter fine-tuning at specific network nodes (master node or secondary node) rather than requiring system-wide changes. Each node can independently analyze failure reports and adjust local handover parameters, improving adaptability while containing implementation complexity to specific system components.
Solution Approach 2:
The patent implements dynamic parameter adjustment where handover parameters are continuously fine-tuned based on real-time failure categorization results. The system adapts parameters such as handover thresholds, timing, and cell selection criteria dynamically, improving versatility while managing complexity through automated adjustment algorithms rather than manual configuration.
Data Source
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AI summary
With MR-DC, UE is connected to both MCG and SCG. When an MCG handover failure occurs, there is a defined method to categorize the handover failures and take corrective actions, however, for SCG handover failures, there are no defined categorizations and corresponding corrective actions currently available. The current method facilitates identification and categorization of SCG handover failures to be categorized as too early, too late and wrong cell handovers. By fine-tuning the handover parameters (based on the SCG handover failure type) SCG handover failure rates would be reduced significantly.