Deep Reinforcement Learning-Based Beam Tracking for Low-Latency Services in Vehicular Networks

13 Feb 2020Yan LiuZhiyuan JiangShunqing ZhangShugong Xu

Ultra-Reliable and Low-Latency Communications (URLLC) services in vehicular networks on millimeter-wave bands present a significant challenge, considering the necessity of constantly adjusting the beam directions. Conventional methods are mostly based on classical control theory, e.g., Kalman filter and its variations, which mainly deal with stationary scenarios... (read more)

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