mmWave Vehicular Communication

Millimeter-wave (mmWave) vehicular communication aims to leverage the high bandwidth of mmWave frequencies for high-speed, low-latency communication between vehicles and infrastructure, enabling advanced driver-assistance systems and autonomous driving. Current research heavily focuses on mitigating the challenges of mmWave's susceptibility to blockage and high mobility, employing machine learning techniques like recurrent neural networks and contextual bandits for beamforming and channel prediction, often incorporating multi-modal sensor data (camera, radar, LiDAR) for improved accuracy and reduced overhead. These advancements are crucial for realizing the full potential of connected and autonomous vehicles, improving safety, efficiency, and overall transportation system performance.