Wireless Network Parameter Conflict Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current network planning and optimization for wireless networks are manual, resource-intensive, and infrequent, leading to suboptimal resource utilization, revenue loss, and degraded service quality due to conflicts between optimization recommendations and the need for frequent manual intervention.
Innovation Solution
An automated system for optimizing wireless network parameters that identifies critical zones, evaluates and resolves conflicts between modifications, and continuously adjusts network settings to maximize performance, using a processor-driven method to store and apply modification groups to cell sites or sectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual network planning and optimization is performed periodically, then network performance can be improved, but the process consumes high human resources and takes long periods between implementations
Solution Approach 1:
The system enables self-service by automatically detecting degraded communication conditions, calculating modifications to network parameters, evaluating conflicts between modifications, and implementing optimizations without requiring manual human intervention. The network optimization system continuously monitors and adjusts itself, freeing human resources while maintaining high optimization frequency.
Solution Approach 2:
The system implements feedback by continuously monitoring communication quality in the wireless network, comparing actual performance against expected performance, and using this information to automatically trigger optimization processes when degradation is detected, creating a closed-loop control system that responds dynamically to network conditions.
2Reliability
If multiple modifications are applied to optimize different cell sites, then network performance can be improved, but conflicts between modifications for the same network parameter can delay optimization
Solution Approach 1:
The system performs preliminary action by evaluating all calculated modifications for conflicts before implementing them. The conflict evaluation step identifies potential conflicts between modifications for the same network parameter and resolves them in advance, ensuring that only non-conflicting modifications are applied together, thus avoiding delays during actual implementation.
Solution Approach 2:
The system applies segmentation by dividing modifications into modification groups based on their compatibility. Modifications that do not conflict are grouped together and applied as a set, while conflicting modifications are separated and resolved individually. This segmentation allows parallel processing of non-conflicting changes while maintaining system consistency.
3Area of stationary object
If network parameters are adjusted to increase coverage area, then more users can be served, but interference to neighboring antennas increases and quality of service deteriorates
Solution Approach 1:
The system applies local quality by calculating and applying different modifications to different cell sites and network parameters based on their specific local conditions. Each cell site's coverage and interference characteristics are analyzed independently, allowing the system to optimize coverage area for each location while applying localized adjustments that prevent excessive interference to specific neighboring antennas, rather than applying uniform changes across the entire network.
Data Source
Figure 1
Figure 2A
Figure 2B
AI summary
Optimizing cell sites or sectors in a wireless network includes calculating modifications to a plurality of network parameters for optimizing wireless network performance; evaluating the modification groups to determine conflicts between modifications for a same network parameter: and eliminating the conflicts between modifications for the same network parameter within the modification groups. The modification groups are used to alter at least one network parameter of the critical ceil sites or sectors, or of a best neighbor ceils sites or sectors for achieving a desired improvement in communications within the wireless network. Optimization is further enhanced by determining the best previous modifications to the wireless network when performance continues to be degraded. Altering wireless network parameters of the critical cell sites or sectors, or the best neighbor cell sites or sectors is performed continuously using the stored modification groups until die desired improvement in communications in the wireless network is achieved.