Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond

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.