Handover prediction: user approach versus cell approach

Knowledge and prediction of system occupancy in wireless cellular systems such as UNITS can play an important role in the optimization of resources allocation procedure. In fact, a resource allocation scheme can make use of such knowledge to anticipate system overloads. On the other hand, studies show that a user´s movements in a cellular network can be predictable. Thus, handover prediction methods can be used to improve resource allocation scheme. Two fundamentally different approaches can be found in handover prediction: cell approaches that make use of global knowledge of user traffic flows in a particular cell; and user approaches that rely on the knowledge of user mobility in short or long term. Short-term methods that predict user speed and location are not studied here. Long-term methods are based on the learning of users´ behaviors by computing profiles for each user. In this paper, we describe two handover predictions methods: cell and user profile based. We also propose a simulation model that enables a comparison of the two approaches.