FINE: Frequency-divided instantaneous neighbors estimation system in vehicular networks

In this paper, we present a novel Frequency-divided Instantaneous Neighbors Estimation (FINE) system specifically designed for density estimation in Dedicated Short Range Communication (DSRC) based vehicular networks. A large amount of vehicular applications such as navigation, traffic control, and data dissemination substantially rely on the density information. Recent works pay great attention to obtain the real-time density information and reduce the occupation time of DSRC channel. The state-of-the-art approach is the Framed Slotted ALOHA (FSA) framework, which benefits from its fine-grained time division design. However, FSA considers only time resource and is unaware of the frequency resource in DSRC. For further accelerating the density acquisition, we propose a frequency-divided approach. The core idea of FINE is to resort fine-grained channel division for parallel neighbors counting. Extensive simulations are conducted to evaluate FINE. The results demonstrate that FINE significantly outperforms existing methods. In a typical dense scenario, FINE reduces the time cost from 2 ms (FSA) to 50 μs, while maintains the accuracy at the same level as FSA.