ML Floorplan Generation for AP Power Management
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Solution Overview
Problem
Effective management of Access Point (AP) power levels across a network to ensure optimal client experiences is challenging due to issues like Overlapping Basic Service Sets (OBSS) and coverage gaps, which existing technologies struggle to address efficiently, especially in complex floor-wide deployments.
Innovation Solution
The implementation of a system that uses machine learning models to generate floor plans by transmitting test frames at unique transmission power levels, incorporating client report data to optimize AP power management, enabling active cooperation between APs and Station (STA) devices to adjust power levels dynamically and reduce interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If AP power is set too high, then coverage area is improved, but interference and OBSS occur causing deteriorated client connectivity
Solution Approach 1:
The system implements a feedback mechanism where APs transmit test frames at different power levels and receive client report data containing RSSI measurements. This feedback loop enables the system to determine optimal power levels by analyzing the relationship between transmitted power and received signal strength, thereby maximizing coverage while minimizing interference and OBSS conditions.
Solution Approach 2:
The patent applies parameter changes by systematically varying transmission power levels across multiple test frames. The system transmits test frames at different power levels (e.g., first power level, second power level) and uses machine learning models to analyze the results, identifying the optimal power parameter that balances coverage area with interference reduction.
2Object-affected harmful factors
If AP power is set too low, then interference is reduced, but coverage gaps emerge leaving areas underserved
Solution Approach 1:
The feedback mechanism collects client report data with RSSI measurements from multiple APs. By analyzing this feedback, the system identifies coverage gaps where signal strength falls below acceptable thresholds, enabling targeted power adjustments that expand coverage without causing excessive interference in already-served areas.
Solution Approach 2:
The system applies local quality by making differentiated power adjustments for different APs based on their specific coverage characteristics. Rather than uniform power reduction, each AP's power level is optimized individually based on local coverage requirements and interference conditions, ensuring adequate coverage in underserved areas while maintaining low interference levels.
3Productivity
If machine learning models are used to optimize power levels, then coverage optimization is improved, but system complexity increases due to standardized frame requirements
Solution Approach 1:
The patent implements universality by designing standardized test frames that serve multiple functions: they carry power level information, enable RSSI measurement, and provide input for machine learning models. This multi-functional approach consolidates what would otherwise require multiple separate communication protocols, reducing system complexity while maintaining advanced optimization capabilities.
Solution Approach 2:
The standardized test frames act as an intermediary mechanism between the control system and client devices. Rather than requiring direct complex interactions between APs and clients for power optimization, the test frames mediate the information exchange, simplifying the overall system architecture while enabling sophisticated machine learning-based optimization.
Data Source
AI summary
Devices, systems, methods, and processes for network device power management at the floor level are described herein. Network devices can communicate with various devices in a wireless network. However, environmental changes, barriers, and other hazards exist in each deployment environment. To better understand each deployment environment, a floorplan can be generated by sending out a plurality of test frames. These test frames can be formatted with power data that is associated with the transmission power level that each test frame is transmitted at. The receiving network device can compare this power data with an actual measurement of the received signals. This data can all be packaged into a client report that can be sent back to the transmitting device which can then process this client report from multiple network devices such that a floorplan can be generated which can be utilized to make more efficient network decisions in the future.