Markov model based location prediction in wireless cellular networks
Tamás Szálka, Sándor Szabó, Péter Fülöp · 2009
The efficient dimensioning of cellular wireless access networks depends highly on the accuracy of the underlying mathematical models of user distribution and traffic estimations. Mobility prediction also considered as an effective method contributing to the accuracy of IP multicast based multimedia transmissions, and ad hoc routing algorithms. In this paper we focus on the trade-off between the accuracy and the complexity of the mathematical models used to describe user movements in the network. We propose Markovian mobility models, in order to utilize the additional information present in the mobile user’s movement history thus providing more accurate results than other widely used models in the literature. The new models are applicable in real-life scenarios, because these rely on additional information effectively available in cellular networks (e.g. handover history), too. The complexity of the proposed models is analyzed and the accuracy is justified by means of simulation. � RESEARCH