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Multi-Dimensional Resource Allocation for Diverse Safety Message Transmissions in Vehicular Networks

机译:车辆网络中不同安全消息传输的多维资源分配

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To enhance driving safety and road intelligence for connected vehicles, the transmission of safety messages is critical in vehicular networks. In this paper, we focus on urban vehicular networks with deployed roadside units, and both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connections can be leveraged for message transmissions. We consider three types of safety messages: periodic messages for vehicular status notification, event-driven messages for urgent situation notification, and messages to achieve collective perception. To support different safety-related services, we develop a multi-dimensional resource allocation scheme to jointly optimize the sensing resource allocation (i.e., selecting vehicles as perception data providers), the V2I/V2V transmission mode selection, and the corresponding communication resource allocation. As the decisions on sensing resource allocation and wireless resource allocation are coupled, an iterative algorithm is proposed to solve the joint optimization problem by taking the differentiated service priorities into consideration. Extensive simulation results are presented to validate the effectiveness of the proposed resource allocation scheme.
机译:为了增强连通车辆的驾驶安全和道路智能,安全消息的传输在车辆网络中是至关重要的。在本文中,我们专注于带有部署路边单元的城市车辆网络,并且车辆到车辆(V2V)和车辆到基础设施(V2I)连接都可以利用消息传输。我们考虑三种类型的安全消息:用于车辆状态通知的周期性消息,发生紧急情况通知的事件驱动消息,以及实现集体感知的消息。为了支持不同的安全相关服务,我们开发了一种多维资源分配方案,共同优化感测资源分配(即,选择车辆作为感知数据提供者),V2I / V2V传输模式选择和相应的通信资源分配。随着对传感资源分配和无线资源分配的决定,提出了一种迭代算法来解决关节优化问题来考虑差异化的服务优先级。提出了广泛的仿真结果以验证所提出的资源分配方案的有效性。

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