User Equipment Mobility Measure Using Cell Weight Parameters
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Solution Overview
Problem
Existing methods for estimating mobility in mobile user equipment are limited, as they require ongoing calls, rely on network-based functionalities, and do not account for cell size differences, leading to inefficient handovers and suboptimal performance, especially during cell reselection in hierarchical cellular systems.
Innovation Solution
A method where user equipment calculates a mobility measure based on broadcasted cell weight parameters and time spent in cells, allowing for more accurate mobility estimation and triggering optimized behavior in high mobility states, even in idle mode, by considering the weighted sum of cell reselections over a specific time period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing mobility estimation methods are used, then mobility can be estimated, but the user equipment must have an ongoing call and rely on network-based functionalities
Solution Approach 1:
The user equipment performs mobility estimation autonomously using locally stored cell weight parameters and measured cell reselection times, without requiring network-based functionality or ongoing calls. The UE calculates the mobility measure itself based on broadcasted cell weight information and its own cell reselection history.
2Measurement precision
If handover-based mobility estimation is used, then mobility can be estimated, but it does not account for cell size differences
Solution Approach 1:
The invention introduces cell weight parameters that represent relative cell sizes, which are broadcast by base stations and stored in the user equipment. These parameters are incorporated into the mobility estimation calculation to account for differences in cell sizes across hierarchical layers, allowing accurate mobility measurement without complex handover analysis.
3Measurement precision
If time spent in cell is used for mobility estimation, then mobility can be estimated, but it requires generalization to weighted sums and timer restarts at layer changes
Solution Approach 1:
The invention simplifies the mobility estimation by using a direct formula that incorporates cell weight parameters and measured cell reselection times, eliminating the need for complex timer restarts at layer changes and generalized weighted sums. The calculation becomes a straightforward application of the broadcasted cell weight information with the UE's own measurement data.
4Measurement precision
If network-based handover history tracking is used, then mobility can be estimated, but it requires main network functionality and broadcast parameters
Solution Approach 1:
The user equipment autonomously performs mobility estimation using locally stored cell weight parameters received through broadcast and its own cell reselection measurements. The UE calculates the mobility measure independently without requiring network-based handover history tracking or ongoing calls, enabling terminal-based mobility management.
Data Source
Figure 1
AI summary
A method for a mobile user equipment (20) to estimate its mobility in a hierarchical cellular mobile system (10) , the system comprising a smaller-sized cell layer (14, 16) and a larger-sized cell layer (12) , the method comprising the steps of receiving cell weight parameters broadcasted from all cells (12a, 14a, 16a) in the hierarchical cellular mobile system (10) , each of which cell reflecting the effective size of the respective cell; and letting the user equipment (20) calculate a mobility measure based on this cell weight parameter and the time it spent camping in the cell.