DFS Channel Selection via Historical Radar Scoring
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Solution Overview
Problem
Conventional wireless devices using DFS channels face challenges due to frequent false radar events and the time-consuming Channel Availability Check (CAC) process, leading to inefficient channel selection and frequent disruptions.
Innovation Solution
Implementing logic that considers the historical data of DFS radar strikes to improve channel selection, allowing wireless devices to learn from past events and make more informed decisions about channel usage, thereby maximizing time on wider channels and minimizing disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If DFS channels are used to expand available bandwidth, then channel capacity is improved, but false radar events cause frequent disruptions and channel switches
Solution Approach 1:
The system performs preliminary Channel Availability Checks (CAC) before utilizing DFS channels and maintains historical records of radar events. By proactively checking channel availability and pre-storing radar event data, the system prepares in advance to avoid disruptions when radar events occur, thus maintaining channel stability while using DFS channels for expanded bandwidth.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring radar events on DFS channels and using this information to make informed channel selection decisions. Historical radar event data is analyzed to identify patterns and avoid channels with high radar activity, creating a closed-loop system that adapts to maintain reliable operation while utilizing available bandwidth.
2Reliability
If Channel Availability Check (CAC) is performed on DFS channels, then channel safety is improved, but the process is time-consuming and reduces productivity
Solution Approach 1:
The system performs CAC checks in advance before channel utilization and stores the results historically. This preliminary action ensures channel safety is verified beforehand, and the stored results can be referenced for future decisions, reducing the need for repeated full CAC processes and improving setup speed.
Solution Approach 2:
Instead of performing complete CAC procedures for every channel selection, the system uses partial verification by checking historical radar event data and applying simplified safety checks. This partial action approach maintains adequate channel safety while significantly reducing the time required compared to full CAC processes.
3Measurement precision
If historical radar event data is collected and analyzed, then channel selection accuracy is improved, but device complexity increases
Solution Approach 1:
The system introduces an intermediary component that maintains historical radar event data and provides processed information to the channel selection algorithm. This intermediary layer handles the complexity of data collection, storage, and analysis, while presenting simplified, pre-processed information to the decision-making process, thus improving accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
Technologies directed to dynamic frequency selection (DFS) avoidance are described. One method stores a timestamp and a first amount of time operating on a channel for each historical radar event detected in a wireless local area network. The method determines a first score using a first weighting factor based on the first amount of time and a second weighting factor based on a second amount of time since the respective historical radar event. The method determines a second score for a first DFS channel by summing the first score for each historical radar event that occurred on the first DFS channel. The method determines a third score for a second DFS channel by summing scores of events occurring on the second DFS channel. The method selects the first DFS channel based on at least the second score and the third score for sending second data to a second device.