Mobility prediction in wireless cellular networks for the optimization of call admission control schemes

In last years there have been a growing interest for cellular networking, due to the availability of different mobile applications and the explosion of mobile devices utilization. If managed in an adequate way, cellular systems with mobile hosts can offer excellent performance and satisfactory QoS levels. In order to avoid service degradations, it is very important to decide whether a new connection can be accepted into the system, with the main aim of maximizing bandwidth utilization while avoiding quality degradations, with more emphasis for non-tolerant applications. Our proposed idea shows how a statistical approach can enhance system performance, without considering a particular prediction scheme (based on Markov theory, neural networks, data mining, Holt-Winters or similars): the proposal has been integrated with a threshold-based statistical bandwidth multiplexing scheme in order to propose the In-Advance Multiplexing Call Admission Control (IAM-CAC) scheme for cellular networks. Simulation campaigns have shown that the performance of the proposed idea in terms of admitted flows, and bandwidth utilization are really acceptable.