A microscopic look at WiFi fingerprinting for indoor mobile phone localization in diverse environments

Abstract

WiFi fingerprinting has received much attention for indoor mobile phone localization. In this study, we examine the impact of various aspects underlying a WiFi fingerprinting system. Specifically, we investigate different definitions for fingerprinting and location estimation algorithms across different indoor environments ranging from a multi-storey office building to shopping centers of different sizes. Our results show that the fingerprint definition is as important as the choice of location estimation algorithm and there is no single combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with WiFi fingerprinting. Our results demonstrate that 5GHz signals are less prone to variation and thus yield more accurate location estimation. We also find that the presence of VAPs improves location estimation accuracy.