Dynamic Wireless Network Parameter Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional wireless networks face performance variations due to changing user traffic patterns, leading to inaccurate predictions and costly adjustments, especially in developing areas where terrain and clutter modeling inaccuracies occur, and existing methods lack dynamic adjustment capabilities.
Innovation Solution
Implement a method that monitors system conditions periodically to determine and adjust network parameters, such as attenuation and antenna settings, either in an open-loop or closed-loop fashion, to improve network capacity and coverage, allowing for dynamic improvements based on real-time feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network parameters are determined in the design phase using statistical or mathematical propagation models, then network performance can be predicted, but the accuracy of predictions deteriorates due to inaccuracy in modeling environment (terrain, clutter, etc.)
Solution Approach 1:
The patent transitions from static design-phase parameters to dynamic real-time adjustment of network parameters. The system continuously monitors system conditions and adjusts network parameters accordingly, making the network adaptive to changing environmental conditions rather than relying on fixed pre-determined parameters.
Solution Approach 2:
The patent implements a feedback mechanism where system conditions are monitored and used to determine subsequent network parameters. This closed-loop approach allows the system to learn from actual performance and environmental conditions, improving prediction accuracy over time by incorporating real-world data rather than relying solely on theoretical models.
2Reliability
If network parameters are adjusted after implementation, then network performance can be improved, but the adjustment process becomes cost- and time-intensive
Solution Approach 1:
The patent enables the network system to automatically adjust its own parameters based on monitored system conditions. This self-service capability eliminates the need for manual intervention by network operators, allowing rapid parameter adjustment without the time and cost associated with human analysis and configuration changes.
Solution Approach 2:
The system performs preliminary monitoring of system conditions and proactively determines optimal network parameters before performance degradation occurs. By continuously analyzing conditions and preparing adjustment decisions in advance, the system can implement changes quickly when needed, reducing both time and cost of adjustments.
3Productivity
If network parameters are adjusted frequently to match changing user traffic patterns, then network performance can be optimized, but the complexity of parameter management increases
Solution Approach 1:
The patent combines multiple functions into a unified system: monitoring system conditions, analyzing traffic patterns, determining optimal parameters, and implementing adjustments are all integrated into a single automated process. This merging simplifies parameter management by consolidating what would otherwise be separate complex tasks into one cohesive system.
Solution Approach 2:
The system is designed to handle multiple network parameters and various system conditions through a single universal framework. Rather than requiring separate management approaches for different parameter types, the patent creates a multi-functional system that can adaptively manage attenuation, neighbor lists, handoff parameters, antenna settings, and other parameters through the same monitoring and determination process.
Data Source
AI summary
In the method, system conditions may be monitored for at least a first time period within a periodic time interval, and network parameters for optimizing a wireless network may be determined. The determined network parameters may be implemented during a first time period within the at least one subsequent periodic time interval.