Cell Site Maintenance Window Optimization via Network Parameter Aggregation
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Solution Overview
Problem
Current telecommunications network maintenance often disrupts network performance, especially during critical upgrades, as vendors typically perform service impacting work during low activity periods, which is no longer feasible due to continuous technology adoption, necessitating a method to minimize network impact during maintenance.
Innovation Solution
A service management system identifies candidate maintenance windows and confidence indicators by aggregating network parameters to determine optimal downtime periods for cell site upgrades, reducing performance impacts on end users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If service impacting maintenance work is performed during low network activity periods, then network performance impact is minimized, but maintenance timing flexibility is reduced
Solution Approach 1:
The system dynamically determines maintenance windows by analyzing real-time network traffic patterns and user behavior data, allowing maintenance scheduling to adapt to changing network conditions rather than relying on fixed historical time slots. This enables the system to identify optimal maintenance periods based on current actual usage patterns.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor network performance metrics, user complaints, and maintenance outcomes to refine and adjust maintenance window predictions over time. This feedback mechanism allows the system to learn from past maintenance experiences and improve future scheduling accuracy.
2Ease of operation
If maintenance windows are determined based on historical traffic patterns, then scheduling simplicity is maintained, but accuracy in identifying optimal maintenance periods deteriorates
Solution Approach 1:
The system performs preliminary analysis of network traffic patterns, user behavior, and application usage data before determining maintenance windows. By pre-processing and aggregating this data in advance, the system builds comprehensive profiles that enable accurate prediction of optimal maintenance periods while maintaining automated simple scheduling operations.
Solution Approach 2:
The patent replaces traditional mechanical rule-based scheduling systems with data-driven algorithms that automatically analyze network parameters and determine maintenance windows. This substitution transforms the scheduling process from a static rule-following mechanism to a dynamic intelligent system that adapts to actual network conditions.
3Measurement precision
If network parameters are aggregated in real-time, then maintenance window identification accuracy is improved, but computational complexity increases
Solution Approach 1:
The system segments network parameter aggregation into hierarchical levels, collecting detailed data at local cell site levels and then aggregating summarized statistics at regional and network levels. This segmentation allows real-time analysis without overwhelming computational requirements at any single level of the system.
Solution Approach 2:
The system transforms raw network parameters into standardized normalized metrics that are easier to process and compare. By changing the form and representation of network data into unified performance indicators, the system reduces computational complexity while maintaining analysis accuracy.
Data Source
AI summary
Systems and methods for generating one or more candidate maintenance windows of at least one cell site of a telecommunications network include a user device and a cell site communicatively coupled to a service management system. The service management system is structured to receive a maintenance request to upgrade the cell site, the maintenance request including a maintenance requirement. The service management system is structured to aggregate one or more network parameters based on the cell site and generate one or more candidate maintenance windows based on the one or more network parameters aggregated and the maintenance requirement. The one or more candidate maintenance windows identify one or more downtime upgrade periods correlating to the cell site.