Wireless Interference Localization Using Field Data Heat Maps
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Solution Overview
Problem
Conventional methods for identifying RF interference sources in wireless telecommunications networks are inefficient, requiring significant human effort and specialized equipment, and struggle with irregular interference patterns that are difficult to pinpoint.
Innovation Solution
A system and method that utilizes wireless stations to collect interference-indicating data, generates a heat map based on free space path loss calculations, and iteratively refines location estimates to quickly identify likely interference sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional manual field searches with directional antennas are used to identify interference sources, then measurement precision can be achieved, but human capital requirements and time consumption increase significantly
Solution Approach 1:
The wireless network performs self-diagnosis by automatically collecting interference-indicating data from multiple wireless stations, calculating free space path loss values, generating heat maps, and identifying interference sources without requiring manual field searches. The system uses its own operational data to locate interference sources autonomously.
Solution Approach 2:
The patent replaces the mechanical manual process of physically canvassing areas with a directional antenna and using a signal generator to manually track interference sources. Instead, the system uses automated computational methods including free space path loss calculations and heat map generation to identify interference locations.
2Measurement precision
If conventional manual field searches are conducted to identify interference sources, then location accuracy can be achieved, but the complexity of equipment and human resources required increases
Solution Approach 1:
The wireless network autonomously performs interference source location using data from its own operational measurements. The system collects interference-indicating data from multiple wireless stations, processes this data through automated algorithms, and generates location estimates without requiring external specialized equipment or human intervention.
Solution Approach 2:
The system creates a virtual representation (heat map) of the physical interference landscape by calculating free space path loss values based on collected data. This digital model allows the system to visualize and analyze interference patterns without physically traveling through the area with specialized measurement equipment.
3Productivity
If automated data collection from multiple wireless stations is used, then productivity increases, but measurement precision may be compromised without proper processing methods
Solution Approach 1:
The system iteratively refines location estimates by using initial heat map results to guide further data collection and analysis. The process continuously improves accuracy by feedback-looping through additional measurements and recalculations until satisfactory precision is achieved, combining automated speed with iterative precision improvement.
Solution Approach 2:
The system changes the parameter of analysis by transforming raw interference measurements into free space path loss values, then into heat map visualizations, and finally into specific location estimates. Each transformation stage processes data differently to extract increasingly specific information while maintaining productivity through automation at each stage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables rapid and accurate localization of interference sources, reducing the need for manual field searches and enhancing network performance by pinpointing interference origins.
Implementation Method 1
generates a heat map based on free space path loss calculations
Data Source
AI summary
A system may receive, from a network, an estimate of coordinates of a location of a potential interference source; determine, based in the estimate, whether the system is within a first threshold distance from the location; if the system is with the first threshold distance from the location, obtain real-time interference data from the network; determine, based on the real-time interference data, whether a source of interference exists near a first location that is within a second distance from a second location specified by the real-time interference data; and send a reply that indicates a result of the determination to the network.


