Automatic Access Point Logical Map Generation
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Solution Overview
Problem
Network administrators manually plot and adjust access point layouts, which is time-consuming and inefficient, especially when dealing with varying wireless station loads and coverage areas.
Innovation Solution
Automatically generating logical maps for access point layouts by plotting access points, determining connection line lengths based on RSSI values, and scaling connection lines to estimate distances between access points, allowing for relative mapping without manual effort and identification of dead spots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual plotting and adjustment of access point layouts is performed, then accurate coverage area mapping can be achieved, but time consumption and administrative effort increase significantly
Solution Approach 1:
The system enables access points to automatically report their own locations and coverage characteristics to the controller, eliminating the need for manual administrator visits. Each access point self-measures RF signals and transmits this data automatically, allowing the network to maintain accurate layout maps without human intervention.
Solution Approach 2:
The patent replaces manual mechanical plotting methods with automated electronic signal measurement and processing. Instead of administrators physically visiting locations and manually recording data, the system uses RF signal exchanges between access points to automatically determine relative positions and generate layout maps through electronic computation.
2Adaptability or versatility
If access points are manually relocated to adjust coverage or handle varying loads, then network optimization can be achieved, but the layout revision process becomes time-consuming
Solution Approach 1:
The system continuously monitors RF signal conditions and automatically detects when access points need relocation based on changing network conditions. The controller receives ongoing feedback about signal strength, coverage gaps, and load distribution, enabling dynamic optimization without manual intervention.
Solution Approach 2:
The system performs preliminary analysis of coverage areas and identifies optimal access point positions before actual relocation is needed. By continuously tracking RF conditions and pre-calculating optimal layouts, the system prepares optimization plans in advance, reducing the time required when changes are actually implemented.
3Productivity
If multiple access points are deployed to handle heavy wireless station loads, then network capacity increases, but identifying coverage dead spots and optimizing placement becomes more complex
Solution Approach 1:
The controller performs multiple functions simultaneously: it manages access point deployments, measures RF signals, calculates relative positions, identifies coverage dead spots, and generates optimized layout recommendations. This multi-functional approach consolidates complex management tasks into a single automated system.
Solution Approach 2:
The system adds the dimension of automated RF signal measurement and electronic computation to the physical deployment of access points. Instead of manually managing spatial relationships, the system uses signal strength measurements and mathematical calculations to automatically determine optimal placements and identify coverage issues in the network space.
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 quick generation of relative access point mappings, identifies dead spots, and assesses potential placements without physical adjustments, improving efficiency and coverage visualization.
Implementation Method 1
A first RSSI (radio signal strength indicator) value of the data packet sent from the first access point is received. A second RSSI value of the data packet received at the second access point is received. A distance between the access point pairs is estimated by comparing the first RSSI value to the second RSSI value.
Data Source
AI summary
A logical mapping of a plurality of access points is automatically generated. Each of the plurality of access points is plotted on a logical map. Lengths of connection lines between access points pairs are determined for each of the plurality of access points on the logical map. Connection lines are oriented in combination with adjustments to the plotted access points on the logical map to run connection lines between each of the access point pairs. Some of the access points are part of more than one access point pair as represented by more than one connection line connected to the at least one access point.