QoS Flow Charging for ProSe Services
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Solution Overview
Problem
The existing charging systems for Proximity Based Services (ProSe) in 5G communication technology face challenges in accurately charging for ProSe scenarios, as they struggle to collect and process charging information for Quality of Service (QoS) flows, leading to inaccurate billing.
Innovation Solution
A method where user equipment acquires and transmits charging information based on QoS flows to network-side equipment, which includes configuring charging trigger events and reporting criteria, allowing for accurate generation and transmission of usage information reports through service-based interfaces to charging functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing charging systems are used for ProSe scenarios, then the charging system structure is simple, but the charging information collection and processing accuracy deteriorates
Solution Approach 1:
The charging system is segmented into multiple functional network elements including CHF (Charging Function), CTF (Charging Trigger Function), CEF (Charging Enablement Function), and ProSe function. Each element handles specific charging tasks independently, allowing accurate collection of QoS flow charging information without requiring complete system redesign.
Solution Approach 2:
The CTF and CEF act as intermediary components between the ProSe function and CHF. The CTF collects charging information from ProSe direct communication, and the CEF processes this information before forwarding to CHF, enabling accurate charging without direct complex interactions between all system components.
2Measurement precision
If detailed QoS flow charging information is collected, then billing accuracy improves, but information processing complexity increases
Solution Approach 1:
Charging information is segmented into specific QoS flow parameters including flow identifier, 5QI (5G QoS Identifier), GFBR (Guaranteed Flow Bit Rate), MFBR (Maximum Flow Bit Rate), and usage volume. This segmentation allows precise billing while organizing complex information into manageable structured parameters.
Solution Approach 2:
The system transforms complex charging information into standardized parameters such as PDU session identifier, QoS flow identifier, and usage volume metrics. These parameter changes enable accurate billing representation while simplifying the processing and transmission of detailed charging data through defined interfaces.
Data Source
AI summary
The present application provides a charging method, a user equipment and a network-side equipment. The method comprises: acquiring, by a user equipment, charging information of a quality of service (QoS) flow, wherein the charging information is generated based on a proximity based service provided by the user equipment; and transmitting the charging information to a network-side equipment, wherein the charging information comprises flow information of the QoS flow.