Network Performance Indicator Calculation via GBR and Non-GBR Service Segmentation
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Solution Overview
Problem
Current methods for determining performance indicators in communications networks are inaccurate due to reliance on load estimation based solely on guaranteed bit rate (GBR) services, which fails to account for the dynamic and uncertain rate requirements of non-GBR services, leading to suboptimal network performance optimization.
Innovation Solution
A method and apparatus that acquire bandwidth utilization rates and throughputs of both GBR and non-GBR services to determine load statuses, rate requirements, and subsequently calculate a load-associated key performance indicator (KPI) by considering the service requirement ratios and throughputs across multiple areas within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If load estimation is based solely on GBR service rate requirements, then the KPI model is simpler to implement, but the accuracy of network performance indicator calculation deteriorates
Solution Approach 1:
The patent segments the service types into GBR services and non-GBR services, treating their rate requirements separately. The load estimation model is divided into multiple components that independently evaluate different service types, allowing each segment to be processed with appropriate methods while maintaining overall model accuracy.
Solution Approach 2:
The patent introduces dynamic adjustment mechanisms for rate requirements of non-GBR services based on network load conditions. The model dynamically adapts to changing service patterns and network states, allowing rate requirements to vary with load status rather than remaining static, thereby improving calculation accuracy under different operating conditions.
2Adaptability or versatility
If the KPI model adapts to service changes of mobile users, then the model becomes more versatile, but the complexity of the model increases
Solution Approach 1:
The patent creates a universal load estimation model that can handle both GBR and non-GBR services within a single framework. The model is designed to be multi-functional, accommodating different service types, network conditions, and optimization scenarios without requiring separate models for each case, thus managing complexity while maintaining versatility.
Solution Approach 2:
The patent employs parameter changes to adapt the model to different service conditions. By adjusting key parameters such as rate requirements, weight coefficients, and load thresholds based on service type and network state, the model achieves adaptability without restructuring its fundamental architecture, thereby controlling complexity while responding to service changes.
3Measurement precision
If rate requirements of non-GBR services are considered in load estimation, then the accuracy of load estimation improves, but the calculation complexity increases
Solution Approach 1:
The patent performs preliminary classification and estimation of non-GBR service rate requirements before final load calculation. By pre-processing service data, categorizing services by type and characteristics, and establishing initial rate requirement estimates, the model reduces the complexity of subsequent calculations while maintaining accurate load estimation that incorporates all service types.
Data Source
AI summary
The present disclosure provides a method and an apparatus for determining a performance indicator of a communications network. The method includes: acquiring bandwidth utilization rates, throughputs of GBR services, and throughputs of non-GBR services of multiple areas included in a communications network; determining load statuses of the multiple areas according to the bandwidth utilization rates of the multiple areas; determining rate requirements of the non-GBR services of the multiple areas according to the load statuses of the multiple areas, the throughputs of the GBR services of the multiple areas, and the throughputs of the non-GBR services of the multiple areas; determining rate requirements of the GBR services of the multiple areas; determining loads of the multiple areas according to the rate requirements of the GBR services and the rate requirements of the non-GBR services of the multiple areas; and determining a load-associated key performance indicator of the communications network.