Data rate adaptation mechanisms in vehicular networks

Abstract

Although several data rate adaptation mechanisms are available for Wi-Fi networks, the same is not true for vehicular networks and its IEEE 802.11p standard. In this paper, we study and evaluate the Wi-Fi available rate adaptation mechanisms in vehicular scenarios to understand their behaviour and analyse their performance under different conditions, in both urban and highway scenarios. The performance results show that loss differentiation algorithms (AARF-CD and CARA) perform better in dynamic and dense environments when compared with those without loss differentiation (Minstrel). They provide an efficient recovery strategy, since they are capable to distinguish the cause of frame loss. The results have also shown that rate adaptation mechanisms are more sensitive to the density of nodes when compared with other parameters; distance and velocity are the second and the third parameters with larger impact in rate adaptation.