Data Rate Fingerprinting: A WLAN-Based Indoor Positioning Technique for Passive Localization

Received signal strength (RSS)/channel state information (CSI) fingerprinting techniques have been widely adopted for wireless local area network (WLAN)-based indoor localization. However, in most of the RSS/CSI fingerprinting techniques, an application/software has to be installed on the target for uploading RSS/CSI information to the localization system. As a result, RSS/CSI fingerprinting cannot achieve passive localization (application-free), which is an essential requirement in many existing localization systems, especially for commercial and military purposes. In this paper, we propose data rate (DR) fingerprinting to achieve passive localization. DR fingerprinting is compatible with most off-the-shelf wireless fidelity (Wi-Fi) devices and can be directly implemented in the existing WLAN-based localization system without any extra hardware. In DR fingerprinting, DRs are used to replace the RSS/CSI to form fingerprints, since DR information can be directly obtained by access points (APs). However, the inherent features of DR, including low-resolution and serious fluctuation, significantly impair the performance of DR fingerprinting. For implementing DR fingerprinting, we leverage multiple transmission power levels, propose a time-window mechanism with different fingerprint formulations, design a AP switching strategy, and design a new matching algorithm named dynamic nearest neighbors (DNNs). We conducted extensive experiments in a real-world testbed to study the performance of DR fingerprinting. Specifically, we compared DR fingerprinting with the state-of-the-art RSS/CSI fingerprinting techniques. The experimental results illustrate that DR fingerprinting can achieve the localization accuracy that is comparable to that of the RSS/CSI fingerprinting with the additional benefit of achieving passive localization.

I. Introduction

Wireless local area network based indoor localization has attracted increasing research attention for years, as it can offer the basis for various novel mobile applications [1], [2] by utilizing widely deployed infrastructure of WLAN such as wireless fidelity (Wi-Fi) access points (APs) to build low-complexity and cost-effective indoor localization systems. Among various techniques proposed by previous works for WLAN-based indoor localization, the received signal strength (RSS)/Channel State Information (CSI) fingerprinting [3]–[5] is one of the most promising techniques as it is effective in complex indoor environment. RSS fingerprinting uses RSS at different locations to build the fingerprints. Intuitively, the RSS could either (1) be scanned by APs, through detecting the signals sent by a Wi-Fi mobile client/target; or inversely, (2) be scanned by the target, through detecting the signals sent by APs. Since the target may adjust its transmission power to save energy or to enhance the signal quality [6], the RSS collected using method (1) is unstable. In order to collect stable RSS, most of the existing RSS fingerprinting techniques [7], [8] adopt method (2) to collect RSS by setting APs at a fixed transmission power. As a result, a specially designed application/software is required to be installed at the target for scanning and uploading the RSS to the system. However, this requirement renders RSS fingerprinting inapplicable for passive localization.¹

Hereafter, we use RSS fingerprinting to replace RSS/CSI fingerprinting.