Network Slice RRM Reconfiguration for Dynamic Resource Sharing
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Solution Overview
Problem
The fixed RRM policy in network slicing leads to inefficient resource allocation, resulting in wasted dedicated resources and low DRB utilization rates due to the inability to share resources among network slices, especially when they are not in use.
Innovation Solution
A method that involves acquiring quality evaluation indices of radio resource management policies, predicting attribute information based on these indices, and updating the RRM policy dynamically to optimize resource allocation for network slices, enhancing resource utilization and user connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed RRM policy is used to allocate dedicated resources to network slices, then resource isolation and service level agreements are ensured, but resource utilization efficiency deteriorates because dedicated resources cannot be shared with other network slices when not in use
Solution Approach 1:
The patent transforms the static fixed RRM policy into a dynamic policy that can be adjusted in real-time based on actual network conditions. The system continuously monitors resource usage patterns and automatically adjusts the allocation of dedicated resources, allowing network slices to share resources when not in use while maintaining isolation when needed, thus resolving the contradiction between reliability and resource waste
Solution Approach 2:
The patent changes the parameters of the RRM policy from fixed values to dynamic values that can be adjusted based on quality evaluation indices. By modifying allocation ratios, time schedules, and resource configuration parameters, the system enables flexible resource sharing while maintaining service level agreements, addressing both resource isolation requirements and utilization efficiency
2Reliability
If dedicated resources are allocated to each network slice according to fixed RRM policy, then service level agreements are met, but DRB utilization rate deteriorates due to inability to share resources among slices
Solution Approach 1:
The patent makes dedicated resources multi-functional by enabling them to serve multiple network slices under different conditions. Through dynamic policy adjustment, resources allocated to one slice can be reassigned to another slice when the first slice is not in use, allowing the same physical resources to fulfill service level agreements for multiple slices and thereby improving overall DRB utilization rate
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors resource usage and adjusts RRM policy parameters accordingly. By evaluating actual utilization patterns and quality metrics, the system dynamically optimizes resource allocation to maximize DRB utilization rate while maintaining service level agreements, creating a closed-loop control system
3Ease of manufacture
If fixed RRM policy is configured with specific resource ratios, then initial resource allocation is simplified, but adaptability to changing network conditions deteriorates
Solution Approach 1:
The patent performs preliminary configuration with fixed RRM policies for initial deployment, then automatically transitions to dynamic adjustment based on learned patterns. The system pre-configures baseline resource allocation ratios for ease of deployment, then uses machine learning to predict optimal adjustments, combining the simplicity of fixed configuration with the adaptability of dynamic optimization
Solution Approach 2:
The patent enables the RRM policy to self-adjust based on actual network conditions and quality evaluation indices. The system automatically learns from historical data, predicts optimal resource allocation, and modifies policy parameters without manual intervention, maintaining ease of initial configuration while achieving high adaptability to changing conditions
Data Source
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AI summary
Provided in the embodiments of the present disclosure are a resource configuration method for a network slice, and a base station and a computer storage medium. The method comprises: acquiring a quality evaluation index of each radio resource management policy; determining predicted attribute information of each radio resource management policy according to the quality evaluation index of each radio resource management policy; and updating the corresponding radio resource management policy according to the predicted attribute information, and reconfiguring a network resource for each network slice according to each updated radio resource management policy.