Location updates and probabilistic tracking algorithms for mobile cellular networks

Abstract

In this work, we develop a novel mathematical model to analyze di erent location update protocols for mobile cellular network. Our model can capture many important features of user movements, such as geographically dependent movement, directional movement and nonexponential distribution of cell dwell times. We propose to use the transient method t o p r edict the location of a mobile user. This method is e cient and, more importantly, able to address the temporal change in the current location of a mobile user. Therefore, the accuracy of the prediction of the location of a user can be enhanced. We also propose a new location update protocol which can attain a lower tracking cost and also adapt to di erent mobility patterns. Transient performance analysis is also carried out and the results are compared with other protocols.

A new analytic framework for dynamic mobility management of PCS networks

“…Mobility management issues of multitier PCS networks were analyzed in [17], [18]. A continuous-time Markov mobility model with its state space containing all the cells in a mobile cellular network was recently introduced in [19].…”