In Juniper 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 of RADAR on a DFS (Dynamic Frequency Selection) channel is a clear example of an event-driven RRM action.
DFS channels are regulated frequencies that must be shared with weather, military, and aviation radar systems. Regulatory bodies require wireless devices to immediately vacate a DFS channel when radar activity is detected. When a Juniper Mist AP operating on a DFS channel detects radar signatures, it generates a real-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 as event-driven RRM because:
The channel change is reactive, not predictive
It is triggered by a specific external RF event (radar detection)
It requires immediate action to maintain regulatory compliance and avoid interference
The other options are incorrect for the following reasons:
FCC compliance defines why the change is required, but it is not an RRM system or decision model.
Global optimization refers to long-term RF tuning across the network based on historical performance data, not immediate forced changes.
Reinforcement learning is used by Mist to optimize RF parameters over time through continuous learning, not for mandatory, instantaneous responses to radar events.
Mist RRM combines event-driven actions, AI-based global optimization, and reinforcement learning to deliver both compliance and performance. In the case of radar detection on a DFS channel, the AP’s channel change is driven by a real-time RF event, making event-driven RRM the correct answer.
