Wireless Network Optimization via RF Behavioral Profiling
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Solution Overview
Problem
Optimizing wireless network performance is challenging due to factors like poor design, congestion, software/hardware bugs, device incompatibility, and RF interference, requiring extensive technical expertise and sophisticated tools, and often necessitating human intervention that is not always available.
Innovation Solution
A computer-implemented method and system that captures and analyzes RF signal data to generate fingerprints of network devices and the RF environment, detecting anomalies and automatically determining corrective actions to improve network performance without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual network optimization with expert intervention is used, then network performance can be optimized, but it requires extensive technical expertise and is not always available
Solution Approach 1:
The system enables self-service by automatically capturing RF signal data, generating behavioral fingerprints, detecting anomalies, and determining corrective actions without requiring human expert intervention. The wireless network optimizes itself through automated analysis of device behaviors and RF environment characteristics.
Solution Approach 2:
The patent replaces the mechanical system of manual expert intervention with an automated electronic system that uses RF signal capture, fingerprint generation, and anomaly detection algorithms to perform network optimization tasks that previously required human expertise.
2Extent of automation
If automated fingerprint analysis is implemented, then continuous monitoring without human intervention is achieved, but system complexity increases
Solution Approach 1:
The system performs preliminary action by continuously capturing RF signal data and generating behavioral fingerprints in advance, so that when anomalies occur, the analysis is already prepared and immediate corrective actions can be determined without waiting for manual intervention.
Solution Approach 2:
The system implements feedback by continuously monitoring RF signals, comparing actual device behaviors against established fingerprints, detecting deviations, and automatically determining corrective actions. This closed-loop feedback enables continuous automated optimization.
Data Source
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Figure 3
Figure 4A
AI summary
Computer-implemented methods and systems are disclosed for optimizing the performance of wireless networks by automatically capturing wireless traffic and other radio frequency (RF) signal data in the network and analyzing the data to identify network anomalies and to determine one or more solutions, without human intervention.