Base Station Self-Optimization for 5G Handover Failures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Enhanced mobility schemes in 5G networks face challenges in supporting robustness during handover processes, leading to radio link failures and increased labor costs for operators.
Innovation Solution
Implementing self-configuration and self-optimization methods in base stations to identify and address the reasons for handover failures, such as too early or late handovers, wrong cell selections, and inappropriate candidate cell configurations, by analyzing UE RLF reports and adjusting handover strategies accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration and optimization of handover parameters is performed, then handover robustness can be improved, but operator labor costs increase
Solution Approach 1:
The base station automatically analyzes UE RLF reports to identify handover failure causes and adjusts handover parameters without operator intervention. The system self-configures handover strategies by detecting patterns in failure data and autonomously optimizing parameters like handover thresholds and timing, eliminating manual configuration while maintaining handover robustness.
Solution Approach 2:
The system continuously monitors handover performance through UE RLF reports and uses this feedback to automatically adjust handover parameters. By analyzing failure patterns and implementing corrective parameter changes, the system creates a closed-loop optimization process that improves handover robustness dynamically without requiring manual operator input.
2Measurement precision
If automated analysis of UE RLF reports is implemented, then handover failure identification accuracy improves, but base station processing complexity increases
Solution Approach 1:
The base station extracts only the essential and relevant information from UE RLF reports for analysis, such as handover-related failure indicators and timing data. By focusing on specific critical parameters rather than processing the entire report, the system achieves accurate failure identification while minimizing processing complexity and computational overhead.
3Reliability
If handover parameters are adjusted based on RLF report analysis, then service continuity is improved, but handover process dynamics increase
Solution Approach 1:
The system dynamically adjusts handover parameters based on real-time analysis of UE RLF reports, adapting to changing network conditions and failure patterns. By making handover strategies flexible and responsive rather than static, the system maintains service continuity while accommodating varying operational requirements through automated parameter optimization.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
The present disclosure relates to a base station that supports self-configuration and self-optimization and a method thereof. A method performed by a target base station in a mobile communication system includes: receiving a radio link failure (RLF) report of a user equipment (UE) from a source base station or a third base station; detecting a reason for an occurrence of a failure based on the RLF report of the UE; and transmitting a message to the source base station based on the detected reason for the occurrence of the failure.