| ID | 原文 | 译文 |
| 3273 | 针对上述问题，在视距路径损耗模型和干扰模型下分析网络的连通性，通过对车联网链路在真实世界的表征，设计动态生长（DN）算法。 | To solve theabove problems, the network's connectivity was analyzed under the line of sight path loss model and the interferencemodel, and the dynamic growth (DN) algorithm was designed through the characterization of the IoV link in the realworld. |
| 3274 | 对车辆节点进行增加、删除和链路的偏好连接后，构建无标度车联网。 | Moreover, a scale-free VANET was built through the network's addition and deletion of nodes and link preferenceconnections. |
| 3275 | 通过仿真结果分析，网络整体的连通性提升了 16%。 | Simulation results indicate that the overall connectivity of the network is improved by 16%. |
| 3276 | 研究了高动态、资源受限条件下的卫星通信系统资源调度问题。 | The resource scheduling problem of satellite communication systems under the condition of high-dynamic andresource limitation was studied. |
| 3277 | 以时间窗口、卫星功耗、信道数量、用户优先级以及任务突发性为约束，建立了卫星资源调度模型。 | A resource scheduling model for satellite communication systems was established basedon time window, energy consumption, number of channels, user priority and task suddenness. |
| 3278 | 考虑到传统的蚁群优化算法存在初期搜索速度过慢、局部搜索能力较弱以及易陷入局部最优等缺点，提出了以初始解集构造、额外信息素沉积为核心的改进蚁群优化算法，来求解资源调度问题。 | Considering the disadvan-tages of slow initial search speed and weak local search ability, the improved ant colony algorithm based on constructionof initial solution set and extra pheromone deposition was proposed to solve the resource scheduling problem. |
| 3279 | 仿真实验评估了所提资源调度算法在完成任务的数量、优先级和调度完成时间方面的性能。 | The opti-mization characteristics of the number of completed tasks, priority and scheduling completion time were simulated andanalyzed. |
| 3280 | 实验结果表明，所提算法具有较快的收敛速度，且与同类型优化算法相比具有更高的调度效率，适用于调度面向密集多波束组网需求的卫星通信系统资源。 | The results show that the algorithm has a fast convergence rate. Compared with the same type optimization al-gorithm, the algorithm has high scheduling efficiency, therefore, it is suitable for scheduling satellite communication sys-tem resources for multi-beam dense networking in the future. |
| 3281 | 在超密集 D2D 通信中，目前的中继选择方案主要假定中继设备具有主动意愿参与数据转发，但部分理性中继设备出于自身考虑，可能会存在时延或拒绝转发的自私行为，进而影响用户体验效果。 | In ultra-dense D2D communication, the current relay selection schemes mainly assume that the relay devicehas the initiative to participate in data forwarding, but some rational relay devices may delay or refuse to forward dueto their own considerations, thus affecting the user experience. |
| 3282 | 从中继设备自私行为角度出发，提出了 D2D 通信中自私中继设备识别方法，进而提出了基于自私行为分析的超密集 D2D 中继选择算法。 | From the perspective of selfish behavior of relay de-vices, a method to identify selfish relay devices in D2D communication was proposed, and then an ultra-dense D2Drelay selection algorithm based on selfish behavior analysis was proposed. |