Wireless AP Channel Configuration Using Monte Carlo Feedback
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Solution Overview
Problem
In densely populated environments, wireless networks face challenges from signal overlap, channel interference, and network congestion due to numerous access points (APs) adjusting configurations in a cascading feedback loop, leading to instability and inefficiency.
Innovation Solution
A Monte Carlo-like algorithm iteratively adjusts AP configurations, measuring quality scores before and after changes, applying probabilistic acceptance to suboptimal states, and dynamically adjusting a tolerance parameter to optimize channel selection, channel width, and signal power, reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple APs adjust configurations to improve individual performance, then signal quality for each AP may improve, but channel interference and network congestion increase due to cascading feedback loops
Solution Approach 1:
The patent implements a coordinated feedback mechanism where APs exchange configuration information and quality metrics with neighboring APs before making configuration changes. This centralized or distributed feedback approach ensures that configuration adjustments by one AP are considered in the context of overall network conditions, preventing cascading feedback loops that cause interference while still allowing individual APs to improve their signal quality through coordinated optimization.
2Adaptability or versatility
If frequent reconfiguration is performed to adapt to changing network conditions, then network optimization improves, but system stability deteriorates due to continuous changes
Solution Approach 1:
The patent implements periodic reconfiguration cycles where APs adjust their configurations at predetermined time intervals rather than continuously or in response to every minor change in network conditions. During each periodic cycle, APs collect quality metrics, evaluate potential configuration changes, and implement optimizations only when significant improvements are expected. This periodic approach allows the network to adapt to changing conditions while maintaining stability during intervals between reconfiguration cycles, preventing the instability caused by frequent continuous adjustments.
3Manufacturing precision
If manual configuration adjustment is performed to optimize individual AP performance, then configuration precision improves, but time consumption and operational complexity increase
Solution Approach 1:
The patent implements self-service automation where APs autonomously monitor their own performance metrics, evaluate configuration options, and adjust their configurations without requiring manual intervention. Each AP collects quality metrics from its own operations and from feedback received from neighboring APs, then automatically determines optimal configuration changes based on predefined optimization algorithms. This self-service approach eliminates the time consumption and operational complexity associated with manual configuration adjustment while maintaining high configuration precision through automated evaluation and selection of optimal settings.
Data Source
AI summary
Systems, methods, and devices for methods for configuring multiple wireless access points (APs) in dense network environments, such as in multi-dwelling units (MDUs). The coordinator, which may be a central server or an elected leader, may be configured to manage multiple APs within a network for comprehensive performance improvements. The coordinator may compute the total quality score based on data from individual APs and determine whether to implement configuration changes, such as by changing configuration parameters for selection, channel width, and signal power.