Velocity-based CRLB predictions for enhanced cooperative links selection in location-enabled mobile heterogeneous networks

In this paper we consider adapting links selection criteria to assist the localization of Mobile Terminals in heterogeneous and cooperative wireless networks. Integrating asynchronously the velocity and location estimates of neighboring terminals in a performance indicator based on a Cramer Rao Lower Bound, one can reliably anticipate on the instantaneous location estimation errors that would be committed along mobile trajectories, while experiencing limited connectivity. This new dynamic indicator is thus helpful to predict in a reasonably short-term the most relevant combination of range measurements, for instance based on Received Signal Strength Indicators, with respect to other neighboring mobile terminals over peer-to-peer links. The idea is to limit in turn power consumption, computational complexity and latency, for instance by postponing as much as possible a complete refreshment of the serving neighbors. Coupling further this selection scheme with a decentralized and cooperative Extended Kalman Filter, simulation results are provided in a realistic dynamic heterogeneous indoor context, including fixed WiFi Access Points and multi-standard WiFi/Zigbee mobile terminals under pedestrian mobility.