2020/07/10 by Nguyen Quang Hieu, Hieu, Nguyen Quang, Dinh Thai Hoang +5
Engineering · #FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI) #Radar Systems and Signal Processing
paper · pdf · doi:10.48550/arxiv.2007.05673
openalex publication_date 2020/07/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This letter introduces an intelligent Real-time Dual-functional\nRadar-Communication (iRDRC) system for autonomous vehicles (AVs). This system\nenables an AV to perform both radar and data communications functions to\nmaximize bandwidth utilization as well as significantly enhance safety. In\nparticular, the data communications function allows the AV to transmit data,≠.g., of current traffic, to edge computing systems and the radar function is\nused to enhance the reliability and reduce the collision risks of the AV, e.g.,\nunder bad weather conditions. The problem of the iRDRC is to decide when to use\nthe communication mode or the radar mode to maximize the data throughput while\nminimizing the miss detection probability of unexpected events given the\nuncertainty of surrounding environment. To solve the problem, we develop a deep\nreinforcement learning algorithm that allows the AV to quickly obtain the\noptimal policy without requiring any prior information about the environment.\nSimulation results show that the proposed scheme outperforms baseline schemes\nin terms of data throughput, miss detection probability, and convergence rate.\n