Estimating position and velocity of mobile terminals in a microcellular network using an adaptive linear regression setup

Mobility tracking yields efficient network resource management and enables very useful additional services, provided that accurate online estimations of both the location and the velocity of a mobile user are performed. We present a novel method for tracing a mobile user by subsequently estimating his/her position through a single base station positioning (SBSP) method designed for microcellular and third generation (3G) wireless communications systems. Raw data about user position are then smoothed through a linear regression setup which adaptively varies its inertia on the basis of the previous observations. This results in a tracking method which is able to estimate both the location and the velocity of a user with high accuracy, as proven by numerical results obtained in different microcellular scenarios.