Systems and methods for classifying an access point (AP) in a wireless fidelity (WI-FI) system

The system classifies Wi-Fi access points using machine learning to improve localization accuracy by distinguishing static and non-static APs, addressing dynamic challenges and enhancing network management, thereby improving user experience and system reliability.

WO2026135331A1PCT designated stage Publication Date: 2026-06-25SAMSUNG ELECTRONICS CO LTD
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
SAMSUNG ELECTRONICS CO LTD
Filing Date
2025-12-18
Publication Date
2026-06-25

AI Technical Summary

Technical Problem

Wi-Fi fingerprint-based localization systems face challenges due to the dynamic nature of non-static access points, signal instability, environmental interference, data overhead, reduced scalability, power constraints, and inaccurate indoor localization, particularly in environments with high mobility, leading to inconsistent RSSI patterns and reduced accuracy.

Method used

A system and method for classifying access points (APs) using machine learning to distinguish between static and non-static APs based on signal parameters, sensor information, and historical data, enabling accurate localization by excluding non-static APs from fingerprint databases and integrating a one-bit mobility indicator into the 802.11k neighborhood report.

Benefits of technology

Enhances localization accuracy by improving network selection, roaming stability, and location precision by distinguishing between static and non-static APs, reducing errors and optimizing network management, thus enhancing user experience and system reliability.

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Abstract

A system and a method for classifying an access point (AP) in a wireless fidelity (Wi-Fi) system are disclosed. The method includes: receiving, by a station, at least one signal parameter associated with the Wi-Fi system by performing a signal scanning of at least one available AP in an area of the station; processing the received at least one signal parameter and sensor information; and determining a mobility status of the at least one available AP in the area of the station, wherein the mobility status is determined by classifying the at least one available AP as at least one of: a static AP and a non-static AP based on an analysis of the received at least one signal parameter, the sensor information, and historical data using at least one data driven model.
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