ID 原文 译文
25075 车联网对于超高可靠与低时延通信(Ultra-Ｒeliable and Low Latency Communications，UＲLLC)具有严格的要求，特别对于车到基础设施(Vehicle to Infrastructure，V2I)场景，UＲLLC 对传输管理交通状况至关重要。 Internet of vehicles has strict requirements in Ultra-Ｒeliable and LowLatency Communications(UＲLLC). Especially in vehicle to infrastructure (V2I) scenario, UＲLLC is crucial to correctly transport and manage traffic conditions.
25076 3GPP Cellular-V2X(C-V2X)作为现在支撑车联网 UＲLLC 主流的无线技术，仍存在技术挑战。 3GPP Cellular-V2X (C-V2X), as the current mainstream wireless technology supporting the UＲLLC, still has technical challenges．
25077 为进一步提升通信性能，本文在V2I 场景下，基于车载终端、路侧单元(Ｒoad Side Unit，ＲSU)与边缘计算车联网服务器(Internet of Vehicles Server，IoVServer)的交互，设计了一种基于 C-V2I 规范的智能信道估计框架。 In order to further improve the communication performance, this paper designs an intelligent channel estimation framework based on C-V2I specification based on the interaction between vehicle terminal, road side unit (ＲSU) and edge computing Internet of Vehicles server (IoV Server) in V2I communication scenario.
25078 在 IoV Server 中，本文提出了一种基于深度学习的信道估计算法，该算法利用一维卷积神经网络(One Dimensional Convolution Neural Network，1D CNN)完成频域插值和条件循环单元(Conditional Ｒecurrent Unit，CＲU)进行时域状态预测，通过引入额外的速度编码矢量和多径编码矢量跟踪环境的变化，对不同移动环境下的信道数据进行精确训练。 In IoV Server, this paper proposes a channel estimation algorithm based on deep learning, which uses one-dimensional convolutional neural network (1DCNN) to complete frequency-domain interpolation and conditional recurrent unit (CＲU) to predict the time-domain state. By introducing additional velocity coding vector and multipath coding vector, the channel data in different mobile environments are accurately trained．
25079 最后通过系统仿真与分析表明，所提算法能够通过信道参数编码追踪不同高速移动环境下的信道变化，实现对信道数据的精确训练。 Finally, system simulation and analysis show that the proposed algorithm can track the channel changes in different high-speed mobile environments through channel parameter coding, and realize the accurate training of channel data.
25080 与车联网代表性信道估计算法相比，所提算法提升了信道估计精度，降低了误码率和增强了鲁棒性。 Compared with the representative channel estimation algorithms in the IoV, the proposed algorithm improves the channel estimation accuracy, reduces the bit error rate and enhances the robustness．
25081 自动驾驶车辆的普及是城市交通发展的重要趋势，然而以交通灯为代表的现有调度方案难以指导这些车辆高效通过十字路口。 Connected and automated vehicles (CAVs) will become the mainstream of urban traffic． However, the existing scheduling schemes, such as traffic lights, are difficult to guide CAVs to pass through intersections efficiently．
25082 为此，本文设计了一种基于顺序选择的无交通灯十字路口调度方案以提高自动驾驶车辆通行效率。 In order to improve vehicle traffic efficiency, a scheduling scheme based on sequential selection is designed for intersections without traffic lights．
25083 首先根据车辆的物理性能对其到达路口的最早时间点进行估算，然后在此基础上寻找车辆可行的计划到达时间点，最终根据计划到达时间为每辆车制定到达路口的行驶计划。 A feasible time for a vehicle to arrive at the intersection is planned according to its physical abilities and status of other CAVs．
25084 在 SUMO(Simulation of Urban MObility)平台上进行的大量仿真实验验证了本文提出方案的有效性。 Extensive simulation experiments are conducted on the SUMO platform to verify the effectiveness of the proposed scheme．