Mobility prediction and spatial-temporal traffic estimation in wireless networks

An understanding of the network traffic behavior is essential in the evolution of today's wireless networks. and thus leads to a more efficient planning and management of the network's scarce bandwidth resources. Prior reservation of radio resources at the future locations of a user's mobile trajectory can help with optimizing the allocation of the network's limited resources, as well as help with sustaining it desirable level of QoS. The objective of this study is to propose a framework for a mobility prediction model using Markov Renewal Processes, for computing the likelihoods of the next-cell transition, along with anticipating the duration between the transitions, for an arbitrary user in a wireless network. The proposed technique can also be used to estimate the expected traffic load and activity at each location in a network's coverage area.