A crowdsourcing and simulation based approach for fast and accurate Wi-Fi radio map construction in urban environment

In order to maintain certain quality of Wi-Fi services even in the congested, uncoordinated ISM bands in urban areas, mobile Wi-Fi clients (i.e. smartphones of pedestrians and vehicle passengers) must be intelligent to carefully choose appropriate access points (APs). For such purpose, Wi-Fi radio map would be of great help to them to make proper AP selections (e.g. vertical handover) along with their movement. However, crowdsourcing-based approaches require a large number of volunteers to monitor and report signals on streets, and war driving is too coarse for accurate map construction in complicated urban building environment. In this paper, we propose a Wi-Fi radio map construction mechanism using both crowdsourcing and highly-precise simulation. Once some cooperative smartphone users collect Wi-Fi beacon data with RSS information, it estimates “tx-tile” for each AP, which is “virtual” transmission source on a wall of the building where AP is inside. Then using this tx-tile with estimated tx-power, it executes online Wi-Fi radio propagation simulations with 3D city models to complement RSS information in many other areas that are not covered by the limited number of cooperative users. We have evaluated the tx-tile localization error and the quality of the radio map. Also we demonstrate our Wi-Fi radio map system for Osaka city.