InJuniper Networks Mist AI Wireless, Radio Resource Management (RRM) uses multiple decision-making systems to adapt the RF environment intelligently. A channel change triggered by the detection ofRADAR on a DFS (Dynamic Frequency Selection) channelis a clear example of anevent-driven RRM action.

DFS channels are regulated frequencies that must be shared with weather, military, and aviation radar systems. Regulatory bodies require wireless devices toimmediately vacate a DFS channelwhen radar activity is detected. When a Juniper Mist AP operating on a DFS channel detects radar signatures, it generates areal-time RF event. This event forces the AP to immediately stop transmitting on that channel and move to a new, non-DFS or alternate DFS channel.

Mist classifies this behavior asevent-driven RRMbecause:

The channel change isreactive, not predictive

It is triggered by aspecific external RF event(radar detection)

It requiresimmediate actionto maintain regulatory compliance and avoid interference

The other options are incorrect for the following reasons:

FCC compliancedefineswhythe change is required, but it is not an RRM system or decision model.

Global optimizationrefers to long-term RF tuning across the network based on historical performance data, not immediate forced changes.

Reinforcement learningis used by Mist to optimize RF parameters over time through continuous learning, not for mandatory, instantaneous responses to radar events.

Mist RRM combinesevent-driven actions,AI-based global optimization, andreinforcement learningto deliver both compliance and performance. In the case of radar detection on a DFS channel, the AP’s channel change is driven by areal-time RF event, makingevent-driven RRMthe correct answer.