Cell Re-Selection Ranking Algorithm for Mobile Devices
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Solution Overview
Problem
Current cell re-selection methods in mobile devices are inefficient and prone to incorrect evaluations, leading to excessive power consumption and suboptimal cell changes, as they require frequent decoding of suitability parameters from candidate cells, which can result in missed opportunities for better network connections.
Innovation Solution
A method that allows mobile devices to evaluate candidate cells using pre-selected parameters applicable to priority-based re-selection algorithms, minimizing the need for frequent tuning and decoding by using stored suitability parameters and measuring signal attributes to determine suitability for re-selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the mobile device frequently tunes to candidate cell frequencies and decodes suitability parameters, then cell re-selection accuracy is improved, but power consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-decoding suitability parameters from candidate cells and storing them in the mobile device. This allows the device to perform cell re-selection evaluations using stored parameters without repeatedly tuning to candidate cell frequencies and decoding parameters each time, thereby reducing power consumption while maintaining re-selection accuracy
Solution Approach 2:
The patent uses copying by creating and storing copies of suitability parameters from candidate cells in the mobile device's memory. These copied parameters (such as Qrxlevmin, Qqualmin, and other cell-specific parameters) are then reused for multiple re-selection evaluations, eliminating the need for repeated decoding operations and reducing energy consumption
2Use of energy by moving object
If the mobile device uses stored suitability parameters from previous decoding, then power consumption is reduced, but re-selection accuracy may deteriorate due to parameter obsolescence
Solution Approach 1:
The patent implements feedback by monitoring the validity and freshness of stored suitability parameters. The mobile device determines whether stored parameters are still applicable to current candidate cells before using them, and updates parameters when changes are detected. This feedback mechanism ensures re-selection accuracy is maintained while still benefiting from reduced power consumption through parameter reuse
Solution Approach 2:
The patent applies dynamics by making the parameter storage and reuse mechanism adaptive. The mobile device dynamically determines when to use stored parameters versus when to perform fresh decoding based on current network conditions and parameter validity assessments. This dynamic approach balances power consumption reduction with maintaining re-selection accuracy
3Reliability
If the mobile device evaluates all candidate cells using decoded parameters, then re-selection reliability is improved, but the complexity of the re-selection process increases
Solution Approach 1:
The patent applies segmentation by dividing the cell re-selection process into distinct phases: parameter decoding, parameter storage, parameter validation, and re-selection evaluation. By segmenting the process and using stored parameters for the evaluation phase, the patent maintains reliability through systematic processing while reducing the complexity of repeated full decoding operations
Data Source
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AI summary
In accordance with one embodiment, there is provided a method for use by a wireless cellular telecommunications device camped on a first cell. The method comprises, at the device: selecting a parameter applicable to a priority-based re-selection algorithm and also applicable to another cell; measuring an attribute of a signal received from a second cell; and, evaluating the second cell for re-selection according to a ranking algorithm based at least on the selected parameter and the measured attribute. A device and computer readable medium are also provided.