Wireless Channel Plan Determination Using Distribution Vectors
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Solution Overview
Problem
Current wireless network channel plan determination methods are time-consuming and resource-intensive, requiring extensive computations and frequent re-adjustments, which hinder efficient network resource utilization.
Innovation Solution
A method for determining channel plans in multiple stages, using a channel distribution vector and set of constraints to optimize channel assignments, reducing computation time and improving network efficiency by iteratively computing cost metrics and adjusting channel priorities based on interference and radar events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional channel plan determination methods are used, then channel assignments can be made, but the computation time and resource consumption are excessive
Solution Approach 1:
The channel plan determination process is divided into multiple stages: initial channel plan generation, cost metric computation, and iterative refinement. Each stage processes specific aspects of channel assignment independently, reducing the computational burden of any single stage and enabling parallel processing where applicable.
Solution Approach 2:
The system pre-computes cost metrics for different channel assignments based on historical interference patterns and radar event probabilities before actual channel plan implementation. This preliminary computation allows for faster real-time decision-making when channel adjustments are needed.
2Productivity
If frequent re-adjustments of channel plans are made to optimize performance, then network efficiency improves, but computation time and resource consumption increase
Solution Approach 1:
The system continuously monitors actual channel performance, interference levels, and radar events, then feeds this information back into the cost metric computation. This feedback mechanism enables targeted re-adjustments only when performance degradation is detected, rather than frequent comprehensive re-optimizations.
Solution Approach 2:
The channel plan determination system adapts its computation frequency and depth based on changing network conditions. During stable periods, computations are performed less frequently; during periods of change or interference, the system dynamically increases computation intensity to maintain optimal performance.
3Reliability
If comprehensive cost metric computations are performed for all channel assignments, then optimal channel plans are achieved, but the process becomes resource-intensive
Solution Approach 1:
The system computes cost metrics with high precision for critical channel assignments (those prone to interference or radar events) while using simplified metrics for less critical assignments. This differentiated approach maintains overall plan quality while reducing total computational resource consumption.
Data Source
AI summary
An example non-transitory computer readable medium comprising instructions executable by a processor to: determine a channel distribution vector based on a channel priority for a plurality of available wireless channels within a wireless network; receive a set of constraints on a channel plan; determine a channel plan meeting the set of user defined constraints based on the channel distribution vector; and transmit the channel plan to a plurality of radios on the wireless network, wherein the channel plan comprises a channel assigned to each radio of the plurality of radios.