Dynamic Radio Resource Model Switching for Lower Compute Use
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Solution Overview
Problem
Existing radio resource management models in wireless networks are deployed statically, leading to unnecessary computational power consumption and heating when they do not provide performance gains in certain scenarios, despite their complexity.
Innovation Solution
Implement a dynamic approach to radio resource management that determines performance benefits of models based on network scenarios, allowing switching from complex to simpler models when necessary to conserve computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex radio resource management models are deployed statically, then network performance optimization is improved, but computational power consumption and heating increase unnecessarily
Solution Approach 1:
The patent applies dynamics by transitioning from static model deployment to dynamic model selection. The system continuously monitors network conditions (traffic load, interference levels, cell utilization) and adapts the complexity of RRM models in real-time. When network conditions are simple, simpler models are used; when conditions are complex, more sophisticated models are deployed, thereby optimizing computational power consumption while maintaining network performance.
Solution Approach 2:
The patent changes the parameter of model complexity based on network conditions. By adjusting the sophistication level of RRM models according to measured network parameters (traffic patterns, load levels, interference characteristics), the system achieves optimal balance between performance optimization and computational energy consumption.
2Reliability
If complex radio resource management models are deployed statically, then network performance optimization is improved, but heating increases unnecessarily
Solution Approach 1:
The system dynamically adjusts model complexity based on actual network conditions, reducing computational load and associated heat generation during periods when simple models suffice. This dynamic adaptation prevents unnecessary heating while maintaining network performance optimization when needed.
3Adaptability or versatility
If complex radio resource management models are used, then radio resource management capability is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic model complexity adjustment, selecting between simple and complex RRM models based on network conditions. This allows the system to maintain high adaptability and versatility when needed while reducing operational complexity during normal conditions, achieving an optimal balance between capability and complexity.
4Productivity
If complex radio resource management models are deployed statically, then performance optimization capability is improved, but unnecessary computations occur
Solution Approach 1:
The system dynamically determines when complex RRM models are actually needed by monitoring network conditions. By switching between simple and complex models based on real-time measurements, the system eliminates unnecessary computations while preserving performance optimization capability when network conditions warrant it.
Data Source
AI summary
The present disclosure relates to a system for use in a wireless network, the system including: a processor configured to determine a performance parameter representative of a performance of a model of radio resource management, the model operating on a radio access network environment; and a radio resource manager configured to perform radio resource management dependent on the performance parameter.