Millimeter wave (mmWave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5G and beyond. To realize applications in future vehicular communications, it is important to take a robust mmWave vehicular network into consideration. However, one challenge in such a network is that mmWave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure (V2I). Moreover, traditional real-time channel estimation strategies are unavailable because vehicle mobility leads to a fast variation mmWave channel. To overcome these issues, a channel estimation approach for mmWave V2I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast time-varying channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the time-varying channel prior information (PI). Finally, by exploiting the PI and the characteristics of the channel, the time-varying channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mmWave time-varying vehicular system.

毫米波 (mmWave) 被认为是 5G 及以后高带宽车载通信的可行解决方案。为了在未来的车载通信中实现应用，重要的是要考虑一个强大的毫米波车载网络。然而，这种网络中的一个挑战是毫米波应该在车辆或车辆到基础设施 (V2I) 之间提供超快速和高速率的数据交换。此外，传统的实时信道估计策略不可用，因为车辆移动性会导致毫米波信道的快速变化。为了克服这些问题，本文提出了一种用于毫米波 V2I 通信的信道估计方法。具体地，通过考虑快速移动的车辆场景，首先建立对应的快速时变信道的数学模型。然后，基站和每个移动用户之间的时间变化规则和确定的到达方向用于预测时变信道先验信息（PI）。最后，利用PI和信道特性，估计时变信道。仿真结果表明，本文提出的方案在毫米波时变车载系统的归一化均方误差和和速率性能方面均优于传统方案。