Mobility prediction algorithm for mobile ad hoc network using pedestrian trajectory data

In the last years mobile ad hoc networks (MANET) has became a hot research subject. MANET is compound by mobile nodes that can be carried by people; the network formed by these nodes has then a highly changing topology. Nodes move according to people mobility patterns and a big number of the network tasks are influenced by nodes mobility. It is reasonable to think that network performance is also highly influenced by mobility. Reduce the uncertainty would have a positive impact on networks performance. In this work we propose a method to dynamically predict a pedestrian position. The method uses recursive least squares lattice adaptive filter to achieve that goal with reasonable low error.