Base Station Parameter Optimization via Cluster Utility Functions
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Solution Overview
Problem
Current communications systems face challenges in efficiently determining and optimizing operating parameters for base stations, leading to suboptimal network performance and increased computational complexity.
Innovation Solution
The system partitions the communications network into clusters, using utility functions to optimize operating parameters for base stations within each cluster, sharing these settings with external stations to reduce computational load and enhance flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system optimizes operating parameters for all base stations simultaneously across the entire network, then network performance is improved, but computational complexity increases significantly
Solution Approach 1:
The patent divides the communications network into multiple clusters, where each cluster contains a subset of base stations. The optimization process is then applied independently to each cluster, significantly reducing the computational complexity compared to optimizing all base stations simultaneously across the entire network.
2Adaptability or versatility
If the system uses utility functions to optimize operating parameters for base stations within clusters, then implementation flexibility is enhanced, but the system complexity increases
Solution Approach 1:
The patent introduces utility functions that take operating parameters as inputs and return optimization results. By changing the parameter representation to utility function outputs, the system achieves implementation flexibility while managing complexity through standardized function interfaces.
3Reliability
If the system shares optimized operating parameters with external base stations, then network-wide performance improves, but information transmission overhead increases
Solution Approach 1:
The patent extracts only the essential optimized operating parameters from the cluster optimization results and shares these with external base stations. This selective information sharing approach reduces the information overhead compared to sharing complete optimization data while still achieving network-wide performance improvements.
Data Source
AI summary
A method for configuring a first base station within a cluster in a communications system having a plurality of cluster includes optimizing an operating parameter of the first base station in accordance with first utility function results from a first utility function associated with the first base station and second utility function results from a second utility function associated with a second base station within the cluster, the first utility function results and the second utility function results according to multiple settings for the operating parameter of the first base station, a first initialized setting of the operating parameter for the second base station, and a second initialized setting of the operating parameter for an external base station outside the cluster. The method also includes sharing the optimized operating parameter with the external base station.