JADE: Zero-Knowledge Device Localization and Environment Mapping for Millimeter Wave Systems

Abstract

Device localization is a highly important functionality for a range of applications. It is particularly beneficial in mmWave networks, where it can be used to reduce the beam training overhead and anticipate handovers between access points. In this paper, we present JADE, an algorithm that estimates the location of a mobile user in an indoor space without any knowledge about the surrounding environment (floor plan, location of walls and presence of reflective surfaces) or about the location and number of access points available therein. JADE leverages the beam procedure used in pre-standard and commercial mmWave equipment to estimate the angle-of-arrival of multipath components of the signal sent by visible access points. This information is then employed to localize the mobile user, estimate the position of access points and finally form a map of the environment. No radar-like ranging operations are required for this. Our results demonstrate that JADE can localize a user with sub-meter accuracy in the broad majority of the cases, and that it even outperforms localization algorithms that require full knowledge of the environment and access point positions.