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Ultra Reliable, Low Latency Vehicle-to-Infrastructure Wireless Communications with Edge Computing

机译:超可靠,低延迟车辆到基础设施与边缘计算无线通信

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Ultra reliable, low latency vehicle-to- infrastructure (V2I) communications is a key requirement for seamless operation of autonomous vehicles (AVs) in future smart cities. To this end, cellular small base stations (SBSs) with edge computing capabilities can reduce the end-to-end (E2E) service delay by processing requested tasks from AVs locally, without forwarding the tasks to a remote cloud server. Nonetheless, due to the limited computational capabilities of the SBSs, coupled with the scarcity of the wireless bandwidth resources, minimizing the E2E latency for AVs and achieving a reliable V2I network is challenging. In this paper, a novel algorithm is proposed to jointly optimize AVs-to-SBSs association and bandwidth allocation to maximize the reliability of the V2I network. By using tools from labor matching markets, the proposed framework can effectively perform distributed association of AVs to SBSs, while accounting for the latency needs of AVs as well as the limited computational and bandwidth resources of SBSs. Moreover, the convergence of the proposed algorithm to a core allocation between AVs and SBSs is proved and its ability to capture interdependent computational and transmission latencies for AVs in a V2I network is characterized. Simulation results show that by optimizing the E2E latency, the proposed algorithm substantially outperforms conventional cell association schemes, in terms of service reliability and latency.
机译:超可靠,低延迟车辆到基础设施(V2I)通信是未来智能城市自主车辆(AVS)无缝运行的关键要求。为此,通过从本地处理来自AVS的所需任务,可以减少端到端计算能力的蜂窝小型基站(SBSS)可以减少端到端(E2E)服务延迟,而不将任务转发到远程云服务器。尽管如此,由于SBSS的有限计算能力,与无线带宽资源的稀缺相结合,最小化AVS的E2E延迟并实现可靠的V2I网络是具有挑战性的。在本文中,提出了一种新颖算法,共同优化AVS-to-SBSS关联和带宽分配,以最大化V2I网络的可靠性。通过使用劳动匹配市场的工具,所提出的框架可以有效地执行AVS的分布式关联,同时占AVS的延迟需求以及SBS的有限计算和带宽资源。此外,已经证明了所提出的算法在AVS和SBS之间进行核心分配的汇聚,其特征在于,其捕获V2I网络中的AVS的相互依存计算和传输延迟的能力。仿真结果表明,通过优化E2E延迟,所提出的算法在服务可靠性和延迟方面基本上优于传统的小区关联方案。

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