This research explores the utilization of relays in vehicle-to-all (V2X) communications, where roadside units (RSUs) alone may not be sufficient to ensure network connectivity due to network congestion, signal attenuation, or interference. By employing stochastic geometry, we analyze a spatially-correlated vehicular network that incorporates both RSUs and relays to serve network users on roads. Our model considers the geometric characteristics of roads, RSUs, relays, and users using random points based on the road structure. Assuming separate frequency resources for RSUs and relays, users can associate with either RSUs or relays. We derive the association probability and coverage probability for the typical user, enabling us to assess network performance. Additionally, we investigate user throughput by considering interactions among different links within the network. This paper offers practical insights for the design of two-tier vehicular networks. Specifically, we express user association, user signal-to-interference ratio (SIR), and user throughput as functions of network variables. This information aids in determining optimal relay density and operating bandwidth to enhance network reliability and maximize user throughput in vehicular networks.

翻译：本研究探讨了中继在车联万物（V2X）通信中的应用——在路侧单元（RSU）因网络拥塞、信号衰减或干扰而不足以保障网络连通性的场景中。通过运用随机几何理论，我们分析了一个包含RSU与中继的空间相关车联网模型，该模型为道路上的网络用户提供服务。我们的模型基于道路结构采用随机点表征道路、RSU、中继及用户的几何特征。假设RSU与中继使用独立频率资源，用户可连接至RSU或中继。我们推导了典型用户的关联概率与覆盖概率，从而评估网络性能。此外，通过考虑网络内不同链路的相互作用，我们研究了用户吞吐量。本文为双层车联网设计提供了实践指导：具体而言，将用户关联、用户信干比（SIR）及用户吞吐量表示为网络变量的函数。这些信息有助于确定最优中继密度与工作带宽，以增强车联网可靠性并最大化用户吞吐量。