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 a 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.