Wireless Mesh Network Correlation for Self-Interference Mitigation
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Solution Overview
Problem
Wireless mesh networks face interference issues due to self-interference, which limits air-time availability and affects network performance, making it challenging to monitor and correlate network conditions with operating parameters effectively.
Innovation Solution
A method and system for correlating wireless network performance parameters with activities and conditions by using test devices to collect and analyze data within the network, allowing for the identification of network conditions and modification of operations to mitigate issues such as air-time availability problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If wireless mesh networks use many wireless links for interconnectivity, then network coverage and connectivity are improved, but self-interference increases and air-time availability decreases
Solution Approach 1:
The patent segments the wireless mesh network into multiple clusters, each managed by a cluster head. This segmentation allows interference management to be localized within clusters rather than affecting the entire network, thereby maintaining connectivity while reducing the impact of self-interference across the network.
Solution Approach 2:
The patent introduces cluster heads as intermediary devices that manage communication within clusters and coordinate with other cluster heads. These intermediaries handle routing and interference management, allowing the network to maintain connectivity while reducing direct interference between wireless links through coordinated scheduling and routing decisions.
2Reliability
If nodes with poor quality wireless links use low-order modulation formats and high packet re-transmissions, then link reliability is improved, but air-time efficiency decreases
Solution Approach 1:
The patent implements local quality adaptation by allowing different modulation formats and transmission parameters to be used in different clusters based on local channel conditions. Cluster heads make localized decisions about modulation formats and re-transmission strategies, optimizing the balance between reliability and air-time efficiency for each specific cluster rather than using uniform parameters network-wide.
Solution Approach 2:
The patent introduces dynamic adaptation of transmission parameters including modulation formats, coding rates, and power levels based on real-time channel conditions. This dynamic adjustment allows the system to optimize the trade-off between link reliability and air-time efficiency by adapting to changing conditions rather than using fixed parameters.
3Productivity
If network conditions are monitored and correlated with operating parameters, then network performance optimization is improved, but system complexity increases
Solution Approach 1:
The patent divides the network into clusters with designated cluster heads that perform monitoring and correlation functions locally. This segmentation distributes the complexity of network monitoring across multiple cluster heads rather than requiring a centralized monitoring system, reducing overall system complexity while maintaining performance optimization capabilities.
Solution Approach 2:
The patent implements self-service monitoring where cluster heads automatically monitor their own cluster's performance parameters and make local optimization decisions without requiring extensive external control. This self-service approach reduces the complexity of external monitoring systems while maintaining the ability to optimize network performance through localized intelligence.
Data Source
AI summary
Methods of correlating wireless network performance of a wireless network are disclosed. One method includes collecting wireless network performance parameters at a location of the network, observing at least one of activities and conditions of the wireless network over the period of time, and correlating the wireless network performance parameters with at least one of the activities and conditions of the wireless network. The wireless network performance parameters can be collected by one or more test devices operating at nodes or clients within the wireless network.