RAN Node Function Selection via Optimization Models
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Solution Overview
Problem
Radio access networks face challenges in optimizing the selection and activation of radio access network (RAN) functions due to resource constraints and varying performance indicators across different base station sites, making it difficult to dynamically adapt functionality to meet specific needs and improve performance efficiently.
Innovation Solution
A method and apparatus that use input data, including configuration and performance information, to select and activate RAN functions based on target performance indicators and resource constraints through an optimization process utilizing prediction models, allowing for tailored functionality adaptation of RAN nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all available RAN functions are activated at a base station, then network performance and functionality are improved, but resource consumption (processing power, storage, memory) increases beyond available constraints
Solution Approach 1:
The system dynamically changes the activation state of RAN functions based on input data, performance indicators, and resource constraints. The optimization process selects which functions to activate by adjusting the parameter of function activation status, thereby achieving optimal network performance within available resource constraints rather than simply activating all or none of the functions.
2Adaptability or versatility
If RAN functions are selected based on manual configuration, then deployment simplicity is maintained, but adaptability to specific base station needs and dynamic performance optimization is reduced
Solution Approach 1:
The system enables self-service by automatically selecting and configuring RAN functions based on input data, performance indicators, and resource constraints. The optimization process autonomously determines which functions to activate without requiring manual configuration, allowing the base station to adapt its functionality dynamically while reducing configuration complexity through automated decision-making.
3Reliability
If RAN functions are activated to meet specific performance targets, then performance indicators are improved, but resource overhead increases
Solution Approach 1:
The optimization process dynamically adjusts the activation status of RAN functions by changing the parameter of function selection based on performance targets and resource overhead constraints. This selective activation ensures that only the necessary functions are running to meet performance requirements, thereby minimizing resource overhead while achieving desired performance levels.
Data Source
AI summary
The present disclosure provides a method of configuring a Radio Access Network (RAN) node to use one or more RAN functions. The method comprises obtaining input data for the RAN node, in which the input data comprises configuration information performance information for the RAN node. Based on the input data, one or more target performance indicators and a constraint on one or more resources for the RAN node, an optimisation process is used to select one or more RAN functions for activation by the RAN node. The optimisation process uses one or more models for predicting, based on the input data and a selection of RAN functions, usage of the one or more resources and a value of the one or more target performance indicators. The RAN node is configured to use the one or more selected RAN functions.