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Vehicle communication is one of the most important use cases in the fifthgeneration of wireless networks (5G). The growing demand for quality of service(QoS) characterized by performance metrics, such as spectrum efficiency, peakdata rate, and outage probability, is mainly limited by inaccurateprediction/estimation of channel state information (CSI) of the rapidlychanging environment around moving vehicles. One way to increase the predictionhorizon of CSI in order to improve the QoS is deploying predictor antennas(PAs). A PA system consists of two sets of antennas typically mounted on theroof of a vehicle, where the PAs positioned at the front of the vehicle areused to predict the CSI observed by the receive antennas (RAs) that are alignedbehind the PAs. In realistic PA systems, however, the actual benefit isaffected by a variety of factors, including spatial mismatch, antennautilization, temporal correlation of scattering environment, and CSI estimationerror. This thesis investigates different resource allocation schemes for thePA systems under practical constraints.

Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications