User Equipment TA List Generation via Algorithmic Extraction
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Solution Overview
Problem
Current mobile communication networks face inefficiencies in managing large lists of Tracking Areas (TAs) for user equipment (UE) registration, leading to increased radio network load and reduced battery life, due to the need to transmit extensive lists of allowed and forbidden TAs, which can result in transmission delays and memory requirements.
Innovation Solution
A method where the UE is provided with an algorithm and input parameters to derive interaction information, allowing it to determine its registration status within a network area without needing to store extensive lists of TAs, and dynamically adjust the size of TA lists to fit within signaling messages, reducing data transmission and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive lists of TAs are transmitted to the UE for registration management, then the UE can maintain accurate registration status across multiple TAs, but the radio network load increases and transmission delays occur
Solution Approach 1:
The patent extracts only the essential parameters needed for TA list generation (such as TA identity, frequency information, and access conditions) from the complete TA list, transmits these condensed parameters to the UE, and enables the UE to locally generate the full TA list. This extraction approach maintains registration accuracy while significantly reducing transmission time and radio network load.
Solution Approach 2:
Instead of the network transmitting the complete TA list directly to the UE (traditional approach), the patent inverts the process by having the network transmit only generation parameters, and the UE performs the TA list generation locally. This inversion shifts the processing burden from the network to the UE, reducing transmission delays while maintaining registration accuracy.
2Reliability
If extensive lists of TAs are transmitted to the UE, then the UE can determine registration status accurately, but memory requirements and battery consumption increase
Solution Approach 1:
The patent extracts and transmits only the essential parameters (TA identity, frequency, access conditions) needed for TA list generation, rather than transmitting the complete TA list. The UE uses these extracted parameters to locally generate the full list, significantly reducing memory requirements and the energy needed for data transmission and storage while maintaining accurate registration status determination.
Solution Approach 2:
The patent enables the UE to self-generate the TA list using received parameters and local processing capabilities, rather than relying on the network to provide the complete list. This self-service approach reduces the UE's memory requirements and battery consumption for storing and managing extensive TA lists while maintaining registration accuracy.
3Adaptability or versatility
If large TA lists are provided to the UE, then the UE can operate across extensive network areas, but signaling message sizes exceed practical limits
Solution Approach 1:
The patent segments the TA list information into two parts: (1) essential generation parameters transmitted in signaling messages from the network to the UE, and (2) the complete TA list generated locally by the UE using these parameters. This segmentation allows the signaling messages to remain compact while the UE achieves comprehensive network area coverage through local expansion of the TA list.
Solution Approach 2:
The patent transitions from transmitting complete TA list data in the signaling dimension to transmitting compact generation parameters and performing local generation in the processing dimension. This dimensional shift enables the UE to access extensive network areas while keeping signaling message sizes within practical limits.
Data Source
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AI summary
A method of operating a communications network and mobile user equipment (UE) in the network includes providing the UE with an algorithm usable with at least one input parameter to derive a quantity of interaction information according to the at least one input parameter, transmitting at least one said input parameter from the network to the UE, using the algorithm with the received at least one input parameter to derive a quantity of interaction information according to the received at least one parameter, and using the derived quantity of interaction information to determine at least one aspect of interaction between the UE and the network.