Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks

Wireless ATM networks require efficient mobility management to cope with frequent mobile handoff and rerouting of connections. Although much attention has been given in the literature to network architecture design to support wide-area mobility in public ATM networks, little has been done to the important issue of user mobility estimation and prediction to improve the connection reliability and bandwidth efficiency of the underlying system architecture. This paper treats the problem by developing a hierarchical user mobility model that closely represents the movement behavior of a mobile user, and that, when used with appropriate pattern matching and Kalman filtering techniques, yields an accurate location prediction algorithm, HLP, or hierarchical location prediction, which provides necessary information for advance resource reservation and advance optimal route establishment in wireless ATM networks.