Wireless Network Capacity Planning via Iterative UE Scheduling
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Solution Overview
Problem
Traditional capacity planning methods for wireless broadband networks are limited by their static and simplistic nature, failing to account for network operation features and actual service characteristics, leading to inaccurate multi-service-related capacity estimation.
Innovation Solution
A method and device that perform access scheduling on User Equipment (UE) based on service type, adjusting network planning parameters to meet capacity requirements by simulating data flows and allocating resources according to Signal to Interference plus Noise Ratio (SINR), ensuring fair scheduling and accurate capacity planning across different service types and network scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional simple ratio method is used for capacity planning, then the planning process is simple and fast, but the accuracy of capacity estimation is insufficient
Solution Approach 1:
The patent transforms the static, one-time ratio calculation into a dynamic iterative process. The system continuously adjusts the number of users and recalculates system capacity through multiple iterations, incorporating feedback from each iteration to improve the accuracy of capacity estimation while maintaining planning efficiency.
Solution Approach 2:
The patent implements a feedback mechanism where the results of each iteration are used to adjust parameters for the next iteration. The system evaluates whether the estimated capacity meets requirements and feeds this information back into the planning process, allowing continuous refinement of capacity estimates until convergence is achieved.
2Ease of manufacture
If static simple estimation is used without network operation features, then the planning method is easy to implement, but it does not reflect actual network operation characteristics
Solution Approach 1:
The patent changes the parameters used in capacity planning from static, generic values to dynamic parameters that reflect actual network operation features. The system incorporates service types, user behaviors, and network conditions as variable parameters that are updated throughout the iterative process, making the planning more reliable while remaining implementable.
3Device complexity
If rough capacity superposition is used for multi-service estimation, then the calculation is simple, but it does not consider actual service characteristics
Solution Approach 1:
The patent segments the multi-service capacity estimation process into distinct components, analyzing each service type separately with its own characteristics and requirements. The system divides the overall capacity planning into service-specific sub-plans, then aggregates them through iteration, achieving accurate multi-service estimation without excessive calculation complexity.
4Ease of operation
If no iterative estimation is performed, then the planning process is straightforward, but it cannot adapt to different network scenes
Solution Approach 1:
The patent introduces dynamics into the planning process through iterative estimation that adapts to different network scenes. The system automatically adjusts its behavior based on the specific scene being planned, modifying parameters and evaluation criteria according to the network conditions, service types, and requirements of each particular scenario.
Data Source
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AI summary
Disclosed are a capacity planning method and device for a wireless broadband network. The method comprises: in a network constructed based on a current network planning parameter that needs to be determined, granting UEs access and scheduling the UEs according to service types of the UEs; making statistics on an index result about the access granting and scheduling on the UEs; and determining whether the index result satisfies a network capacity planning requirement; if yes, determining the current network planning parameter as a target planning parameter; otherwise, adjusting the network planning parameter until the index result about the access granting and scheduling of the UEs satisfies the network capacity planning requirement. The present invention plans network capacity for multiple services according to service features, and improves accuracy of the network capacity planning.