NWDAF Service Preference Prediction for Network Resource Pre-allocation
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Solution Overview
Problem
Existing network resource allocation in 5G networks is inflexible, leading to waste and inefficient utilization of resources, as it fails to effectively predict and pre-allocate resources based on user preferences.
Innovation Solution
The Network Data Analysis Function (NWDAF) acquires historical user data to generate service preference predictions and suggestions, which are then used by network functions to pre-allocate resources, optimizing resource allocation and improving utilization by anticipating future service needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network resource allocation is performed in a flexible manner based on user preferences, then resource utilization efficiency is improved, but system complexity increases due to the need for prediction and pre-allocation mechanisms
Solution Approach 1:
The system performs preliminary actions by predicting user service preferences in advance and pre-allocating network resources before actual service requests occur. The NWDAF analyzes historical data and generates preference predictions, which are then used by the PCF to pre-allocate resources, avoiding the need for complex real-time allocation decisions when services are actually requested.
Solution Approach 2:
The NWDAF (Network Data Analytics Function) serves as an intermediary that collects and analyzes user service data, generating preference predictions that are then transmitted to the PCF (Policy Control Function). This intermediary structure separates the complex prediction functionality from the resource allocation functionality, allowing each component to specialize and reducing overall system complexity.
2Measurement precision
If historical user data is collected and analyzed for preference prediction, then resource pre-allocation accuracy is improved, but data processing time and computational load increase
Solution Approach 1:
The system performs data analysis and preference prediction in advance as a preliminary action, rather than waiting until resources need to be allocated. The NWDAF continuously analyzes historical user service data and generates preference predictions beforehand, so that when the PCF needs to allocate resources, the prediction is already available, reducing actual processing time.
Solution Approach 2:
The system processes user data partially by focusing on specific dimensions relevant to service preferences (such as service types, time patterns, location information) rather than analyzing all possible user data. This selective approach maintains prediction accuracy while reducing computational load and processing time.
Data Source
AI summary
This disclosure provides a network resource pre-allocation method, device, system, and medium, wherein the method includes: an NWDAF acquiring historical record information of a user accessing a service, and generating user service preference prediction and suggestion information according to the historical record information; and the NWDAF sending the user service preference prediction and suggestion information to a network function (NF) so that the NF pre-allocates a network resource according to the user service preference prediction and suggestion information.