GPS-aided Doppler spread estimation in a mobile system

Abstract

Most current Doppler spread (DS) estimators are based on the wireless channel auto-correlation function. In these methods, the DS estimation variance is high, especially due to channel estimation errors. Furthermore, in a time-varying velocity scenario, DS varies over time, which adds extra complexity to the estimation process. In this study, we propose a GPS-aided DS estimation scheme that incorporates accurate velocity information to reduce estimation variance in a mobile system. The Cramer-Rao lower bound method and the maximum likelihood estimation method are used in the proposed estimators. Through simulations, we show that the DS variance is significantly reduced with the proposed estimators.