【摘要】 针对蜂窝车联网系统中不同优先级业务的边路资源自主选择分配，分析了基于参考信号能量的自主选择算法流程，设计了能量门限方程；针对能量方程参数估计问题，将基于能量的自主选择算法与深度Q学习算法结合，通过有限次算法迭代得到能量门限方程的最优参数值。仿真结果表明，基于深度Q学习的边路资源分配算法可以满足不同优先级车联网业务的边路资源需求，同时提高系统分组接收率。更多还原

【Abstract】 For the sidelink resource autonomous selection scheme of different priority services in celluar-vehicle to everything(C-V2X) system, the procedure of autonomous selection algorithm based on reference signal energy was analyzed,and the energy threshold equation was designed. For the energy equation parameter estimation problem, energy-based autonomous selection algorithm was combined with deep Q learning algorithm, and the optimal parameter value of the energy threshold equation was obtained by iteration of the finite-degree algorithm. Simulation results showed that the side resource allocation algorithm based on deep Q learning could ensure the side resource requirements of V2X services with different priorities, and improve the packet reception ratio performance of the system.更多还原