In Vehicular Ad-Hoc Networks, a link failure may occur due to non-optimal channel conditions, congestion or node mobility which causes data loss. Common proposed approaches try to overcome this problem by anticipating link disruptions with MAC layer indicators. Such methods, particularly in urban environments (i.e. highly dynamic) are ineffective. Our aim is to setup an indicator that detects at the PHY level an upcoming link breakage before it causes packet loss at the NET layer. To this end, we use Orthogonal Frequency-Division Multiplexing decoding events that are combined thanks to the Dempster–Shafer Theory (DST). The proposed indicator, called Link Breakage Forecasting Indicator performs for a given link, an analysis based on decoding error density measurements, in order to maintain the link history. The adaptation of the DST to the analyzed phenomena relies on using mass functions controlled by the reception power, the relative speed and the error density. The link failure probability is obtained thanks to the fusion of these heterogeneous information using the cautious combination rule. The later allows to consider data even if it is dependent without providing biased results. Simulation results show that detection times are suitable and robust against mobility related characteristics, such as vehicle speeds and urban environment variability.

在车载Ad-Hoc网络中，链路故障可能是由于非最佳信道状况，拥塞或导致数据丢失的节点移动性而发生的。提出的常见方法试图通过使用MAC层指示符预测链路中断来克服此问题。这样的方法，特别是在城市环境中（即高度动态）是无效的。我们的目标是建立一个指示器，以在PHY级别上检测即将发生的链路中断，然后再引起NET层的数据包丢失。为此，我们使用正交频分复用解码事件，这要归功于Dempster–Shafer理论（DST）。所提出的指标称为“链路中断预测指标”，它针对给定的链路执行基于解码错误密度测量的分析，以维护链路历史记录。DST对所分析现象的适应性取决于使用受接收功率，相对速度和误差密度控制的质量函数。由于使用谨慎的组合规则将这些异构信息融合在一起，因此获得了链路故障概率。后者允许即使不依赖数据也可以考虑数据，而不会提供有偏差的结果。仿真结果表明，检测时间是合适的，并且对与移动性相关的特征（如车速和城市环境变化）具有鲁棒性。后者允许即使不依赖数据也可以考虑数据，而不会提供有偏差的结果。仿真结果表明，检测时间是合适的，并且对与移动性相关的特征（如车速和城市环境变化）具有鲁棒性。后者允许即使不依赖数据也可以考虑数据，而不会提供有偏差的结果。仿真结果表明，检测时间是合适的，并且对与移动性相关的特征（如车速和城市环境变化）具有鲁棒性。