Cellular Mobility Management Using UE Measurements to Curb Ping-Pong Handovers
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Solution Overview
Problem
Current cellular network mobility management systems face challenges in minimizing unnecessary handovers, maintaining signal strength, and reducing quality of service degradation due to signal fluctuations, while managing complexity and ensuring reliability.
Innovation Solution
A system and method utilizing user equipment measurements, including a cellular network mobility management application (CMMA) that generates control-plane and QoS-based handover suggestions, performs signal strength monitoring, and adjusts handover timing to reduce repetitive handovers through anomaly detection and threshold modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If handovers are executed based on current signal strength thresholds, then cellular connectivity is maintained, but repetitive unnecessary handovers occur due to signal fluctuations
Solution Approach 1:
The system forecasts future handover events by analyzing historical signal strength data and UE movement patterns before actual handovers occur. This preliminary action allows the system to pre-execute or postpone handovers based on predicted conditions, preventing repetitive handovers caused by temporary signal fluctuations while maintaining connectivity.
Solution Approach 2:
The system continuously monitors signal strength, QoS metrics, and handover outcomes, feeding this information back into the predictive model. This feedback loop enables the system to learn from past handover decisions and improve future predictions, reducing unnecessary handovers while maintaining reliable connectivity.
2Stability of the object's composition
If handovers are postponed to reduce repetitive transfers, then signal strength stability improves, but QoS degradation may occur
Solution Approach 1:
The system performs preliminary QoS assessments before executing handovers, forecasting future QoS conditions based on historical data and current trends. This allows the system to postpone handovers only when predicted QoS will remain acceptable, preventing both repetitive handovers and QoS degradation.
Solution Approach 2:
The system dynamically adjusts handover thresholds and timing parameters based on real-time QoS measurements and predictive analytics. By changing these parameters adaptively, the system optimizes the balance between signal stability and QoS maintenance for each specific scenario.
3Device complexity
If predictive handover forecasting is implemented, then unnecessary handovers are reduced, but system complexity increases
Solution Approach 1:
The system leverages existing network infrastructure and readily available measurement data (signal strength, QoS metrics, location information) to perform predictive handover forecasting. By using self-generated data and existing computational resources, the system reduces complexity while maintaining high reliability.
Solution Approach 2:
The system replaces complex rule-based handover decision mechanisms with data-driven predictive models that analyze historical patterns. This substitution simplifies the decision-making process by using statistical patterns rather than complex conditional logic, reducing system complexity while improving reliability.
Data Source
AI summary
A system for cellular network mobility management based on user equipment measurements includes a host device, cellular communication cells, and a back office. The host device, cellular communication cells and back office execute a cellular network mobility management application (CMMA). The CMMA as initiated by the host device, generates control-plane measurement event based handover suggestions, generates quality-of-service (QoS) measurement based handover suggestions. Then the CMMA, via the cellular communication cells, performs cellular network signal strength monitoring and determines that a measurement configuration (MC) threshold has been achieved. Subsequently, the system performs anomaly detection; and selectively alters timing of cellular network handovers between the host device and the one or more cellular communication cells to reduce a potential for repetitive handovers from a first level to a second level less than the first level while maintaining or improving a cellular network QoS.