Frame-based mobility estimation via compressive sensing in delay-tolerant vehicular networks

In this paper, we study the problem of estimating mobility trajectories via a small number of measurements from realistic mobility traces. We propose a frame-based solution to estimate the complete mobility trace at the end of the frame. During each frame, a few measurements are transmitted via vehicular communications, and then estimation is performed at the receiver. We propose different sampling schemes to estimate the mobility trajectory at the end of the frame, and we compare it to the actual mobility trace. The proposed scheme is designed as a practical system for vehicular mobility estimation, and is suitable for road traffic management applications. We study the proposed mobility estimation scheme via simulations with realistic mobility traces generated by Paramics simulator [1]. The data are based on a realistic map of the Gardinar Expressway in the city of Toronto. Extensive simulation results shows that the proposed scheme can significantly reduce the number of transmitted samples while providing a good estimate of the mobility traces.