Beam-Based UE Mobility States for Adaptive RRM Power Saving
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Solution Overview
Problem
Existing mechanisms for relaxing Radio Resource Management (RRM) measurements in 5G NR are inefficient and do not account for more refined mobility states based on beam-level changes, leading to unnecessary power consumption in User Equipment (UE).
Innovation Solution
Introduce a Beam-Based UE Mobility State (BBMS) that utilizes beam management to define UE mobility states (stationary, medium, high) and adapt RRM measurements accordingly, with network-configured thresholds to determine relaxation levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RRM measurements are performed frequently and comprehensively to ensure reliable mobility management, then measurement reliability is improved, but UE power consumption increases
Solution Approach 1:
The patent implements dynamic adaptation of RRM measurement parameters based on detected mobility states. The UE continuously monitors beam changes and adjusts measurement frequency, filtering thresholds, and reporting intervals according to whether it is in low, medium, or high mobility state. This dynamic adjustment ensures reliable mobility management when needed while reducing power consumption during stationary periods.
Solution Approach 2:
The patent changes multiple measurement parameters based on mobility state detection including: measurement frequency (from frequent to relaxed), filtering threshold adjustments, reporting interval modifications, and beam change detection thresholds. These parameter changes allow the system to maintain measurement reliability when mobility requires it while significantly reducing power consumption during low-mobility periods.
2Measurement precision
If RRM measurement frequency is increased to improve mobility detection accuracy, then mobility detection precision is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts measurement frequency based on detected mobility state. During low mobility states, measurements are performed at relaxed intervals to conserve power. When mobility state changes to medium or high, the system automatically increases measurement frequency to maintain accurate mobility detection, thus adapting precision to actual needs rather than maintaining constant high-frequency measurements.
Solution Approach 2:
The patent applies partial measurement action by performing comprehensive RRM measurements only when mobility state requires it. During low mobility states, the system performs reduced measurements (partial action) sufficient for stationary conditions. When mobility increases, the system escalates to full measurement frequency to ensure accurate detection, avoiding excessive measurements during stationary periods while maintaining adequate precision when needed.
3Reliability
If the number of measured cells and carriers is increased to improve RRM measurement comprehensiveness, then measurement completeness is improved, but device complexity increases
Solution Approach 1:
The patent dynamically adjusts the scope of RRM measurements based on mobility state. During low mobility states, the UE measures fewer cells and carriers with relaxed criteria, reducing processing complexity. When mobility state changes to medium or high, the system expands measurement scope to include more cells and carriers with stricter criteria, ensuring comprehensive mobility management only when mobility patterns require it.
Solution Approach 2:
The system applies different measurement quality levels to different mobility scenarios. During stationary periods, relaxed measurement quality (fewer cells, longer intervals) is sufficient and applied locally. When mobility increases, higher measurement quality (more cells, frequent measurements) is applied locally to the affected measurement processes. This localized quality adjustment maintains measurement completeness where needed while reducing overall device complexity.
Data Source
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AI summary
The present invention introduces a beam-based UE mobility state estimate for power saving purposes, based on monitoring the distinct beam(s) (302) detected by the UE. In other words, the number N of distinct serving beams changed by the UE within a time window T is monitored (302) against the configured threshold values. If N is below a first threshold value "Thr1", a low/stationary mobility state is determined (303) and the UE applies a first measurement configuration (305) associated with the low/stationary mobility state. If N is between first and second threshold values "Thr1" and "Thr2", a medium mobility state is determined (304) and the UE applies a second measurement configuration (306) associated with the medium mobility state. If N is above the second threshold value "Thr2", a high mobility state is determined and the UE applies a third measurement configuration associated with the high mobility state.