Indoor Positioning with Wi-Fi Location: A Survey of IEEE 802.11mc/az/bk Fine Timing Measurement Research

2025-09-04

AI Summary

A systematic survey of Wi-Fi Fine Timing Measurement (FTM) under IEEE 802.11mc/az/bk for indoor localization remains absent. This paper presents the first comprehensive review of over 180 studies, focusing on FTM and its enhancements—namely, 802.11az high-accuracy ranging and 802.11bk multi-AP coordination—across four dimensions: localization accuracy improvement, multi-sensor fusion (e.g., Wi-Fi/UWB/IMU), machine learning–based modeling, and security mechanisms. Employing a hybrid methodology of taxonomic classification and quantitative performance evaluation, we identify critical technical pathways and bottlenecks toward sub-meter positioning, including channel modeling inaccuracies, clock offset compensation limitations, and vulnerabilities to adversarial attacks. We further articulate three forward-looking research directions for 6G-enabled indoor sensing: standardization, lightweight implementation, and trustworthiness assurance.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Web Mining and Content Analysis: Web measurements

Abstract

Indoor positioning is an enabling technology for home, office, and industrial network users because it provides numerous information and communication technology (ICT) and Internet of things (IoT) functionalities such as indoor navigation, smart meter localization, asset tracking, support for emergency services, and detection of hazardous situations. The IEEE 802.11mc fine timing measurement (FTM) protocol (commercially known as Wi-Fi Location) has great potential to enable indoor positioning in future generation devices, primarily because of the high availability of Wi-Fi networks, FTM's high accuracy and device support. Furthermore, new FTM enhancements are available in the released (802.11az) and recently completed (802.11bk) amendments. Despite the multitude of literature reviews on indoor positioning, a survey dedicated to FTM and its recent enhancements has so far been lacking. We fill this gap by classifying and reviewing over 180 research papers related to the practical accuracy achieved with FTM, methods for improving its accuracy (also with machine learning), combining FTM with other indoor positioning systems, FTM-based applications, and security issues. Based on the conducted survey, we summarize the most important research achievements and formulate open areas for further research.

Problem

• Surveying IEEE 802.11mc/az/bk FTM protocols for indoor positioning
• Addressing the lack of dedicated reviews on Wi-Fi Location enhancements
• Analyzing practical accuracy, methods, applications, and security issues

Innovation

• IEEE 802.11mc FTM protocol for positioning
• Machine learning methods to enhance accuracy
• Integration with other indoor positioning systems