Access Point Self-Positioning via Beacon Trilateration

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing wireless communication systems lack an efficient method for access points to automatically determine and track their location within a positioning system, especially in dynamic environments where manual configuration is impractical.

Innovation Solution

The implementation of an Extended Kalman Filter (EKF) algorithm allows a location-unaware access point to estimate and refine its position using information from location-aware stations, enabling real-time location tracking and movement detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual configuration is used to set access point locations, then location accuracy can be ensured, but the complexity of deployment and maintenance increases significantly

Engineering Contradiction:
Improvelocation accuracyVSAvoiddeployment complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The access point automatically determines its own location by listening to beacon frames from nearby access points with known locations and using trilateration algorithms, eliminating the need for manual configuration. The system self-configures by processing signals from surrounding access points and computing its position based on measured signal powers and known locations of neighboring access points.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The invention uses beacon frames transmitted by neighboring access points as intermediaries to convey location information. These beacon frames contain identifier and location data that the target access point uses to calculate its position, serving as a mediator between known location references and the unknown location to be determined.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Adaptability or versatility

If access points are deployed in dynamic environments where locations change, then adaptability to different environments is improved, but the ability to maintain accurate location information deteriorates

Engineering Contradiction:
Improveenvironmental adaptabilityVSAvoidlocation tracking accuracy
Core Design Contradiction:
Adaptability or versatilityVSReliability

Solution Approach 1:

The access point continuously listens to beacon frames from neighboring access points and continuously updates its location estimate, maintaining uninterrupted location tracking. This continuous operation ensures that location information remains current even as the access point moves or the environment changes, preserving reliability in dynamic conditions.

Inventive Principle:
Principle #20Continuity of useful action

Solution Approach 2:

The system uses feedback from measured signal powers of beacon frames to continuously refine location estimates. By monitoring changes in signal strengths from neighboring access points over time, the system detects movement and triggers location recalculation, creating a feedback loop that maintains accuracy in dynamic environments.

Inventive Principle:
Principle #23Feedback

3Extent of automation

If GPS receivers are installed in access points to obtain location information, then location determination becomes automatic, but the cost and device complexity increase

Engineering Contradiction:
Improvelocation determination automationVSAvoidhardware complexity
Core Design Contradiction:
Extent of automationVSDevice complexity

Solution Approach 1:

The invention replaces the mechanical/GPS-based location determination system with a wireless signal-based system. Instead of using GPS receivers to obtain satellite positioning data, the access point uses wireless beacon frames from neighboring access points to determine location, substituting a complex hardware system with a software-based signal processing approach.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The wireless communication infrastructure serves multiple functions: it provides both data communication and location determination. The same wireless interfaces used for normal network operations are also used to receive beacon frames and calculate location, eliminating the need for separate GPS hardware and achieving automation without additional dedicated components.

Inventive Principle:
Principle #6Universality (Multi-functionality)

4Ease of operation

If trilateration algorithms are used to determine access point location, then location can be determined without manual configuration, but the computational complexity and time required increase

Engineering Contradiction:
Improveconfiguration easeVSAvoidlocation determination time
Core Design Contradiction:
Ease of operationVSLoss of time

Solution Approach 1:

Location determination is performed as a preliminary step during the initial association process between access points. By calculating location before full network operation begins, the system avoids interrupting ongoing communications for location updates, reducing the perceived time loss during normal operation.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system performs location determination only when necessary - triggered by detection of movement or changes in the environment - rather than continuously recalculating at maximum frequency. This partial action approach balances accuracy requirements with computational efficiency, avoiding unnecessary calculations while maintaining location validity.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP2641416B1Self-positioning of a wireless station
Publication Date: 2019.10.02 QUALCOMM INC
  • EP2641416B1 patent drawingFigure 1
  • EP2641416B1 patent drawingFigure 2
  • EP2641416B1 patent drawingFigure 3

AI summary

A self-positioning mechanism is provided that determines and tracks the position of an access point in real time. A location unaware access point determines its location from the locations of location aware stations. The location is determined based on a predicted estimate which is updated based on measured values of the locations of the location aware stations over a time period. The movement of the location is then tracked based on the differences between range measurements of the location aware stations.