Policy and Charging Control Based on Fine-Granularity Location
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Solution Overview
Problem
Current Policy and Charging Control (PCC) frameworks in telecommunication systems, such as those defined by 3GPP, lack the capability to perform policy and charging control based on fine-granularity location information, which is necessary for specialized application scenarios like providing post-paid services or managing network resources in temporary hot-spot cells.
Innovation Solution
The method involves a Policy and Charging Enforcement Function (PCEF) acquiring and reporting location acquisition ability information to a Policy Control and Charging Rules Function (PCRF) through Credit-Control-Request messages, allowing the PCRF to determine and send PCC rules that account for specific user location information attributes like Routing Area Identity (RAI) and 3GPP-User-Location-Info, enabling PCC decisions based on finer location granularity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the current 3GPP PCC framework is used, then the system structure is simple and easy to operate, but the location information granularity is coarse and cannot meet special application scenario requirements
Solution Approach 1:
The patent segments the location information reporting mechanism by introducing different attribute value pairs for different location information types (RAI, CGI, SAI, 3GPP-User-Location-Info). This allows the system to selectively report and process fine-granularity location information only when needed, without requiring complete restructuring of the PCC framework. The segmentation enables gradual enhancement of location precision while maintaining compatibility with existing simple scenarios.
2Measurement precision
If fine-granularity location information is implemented, then service management precision is improved, but information processing complexity increases
Solution Approach 1:
The patent implements a dynamic location information reporting mechanism where the PCEF selectively reports different types of location information (RAI, CGI, SAI, or 3GPP-User-Location-Info) based on availability and service requirements. The PCRF dynamically selects which attribute value pairs to process based on the specific application scenario. This dynamic approach reduces unnecessary information processing while enabling fine-granularity control when needed.
3Reliability
If location acquisition ability information is reported by PCEF, then PCC decision accuracy is improved, but message processing complexity increases
Solution Approach 1:
The patent enhances the existing Credit-Control-Request message to carry multiple types of location information attribute value pairs (RAI, CGI, SAI, 3GPP-User-Location-Info) and location acquisition ability information. This universal message structure can accommodate both traditional coarse-granularity scenarios and new fine-granularity requirements without requiring separate message types. The multi-functionality reduces the need for additional complex message processing logic while improving PCC decision accuracy.
Data Source
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AI summary
A method for implementing a policy and charging control ,PCC, is provided. The method includes: acquiring user location information; and determining a PCC rule of a user according to the acquired user location information. The PCC rule is for a policy and charging enforcement function , PCEF, to perform the corresponding PCC. Corresponding PCEF, policy control and charging rules function, PCRF, gateway, and system for implementing a PCC are also provided. Thus, the PCC based on fine-granularity location information is implemented.