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 Cox point processes conditionally on the same road structure. Assuming disjoint frequency resources for serving users and for enabling RSU-connected relays, each user can associate with either an RSU or a relay whichever is closest to it. 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 proposed 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辆与万物（V2X）通信中的利用，其中单独的路边单元（RSU）可能因网络拥塞、信号衰减或干扰而不足以确保网络连通性。通过采用随机几何，我们分析了一个包含RSU和中继的空间相关车辆网络，用于为道路上的网络用户提供服务。我们的模型利用Cox点过程，基于同一道路结构条件，考虑了道路、RSU、中继和用户的几何特征。假设用于服务用户和用于启用RSU连接中继的频谱资源不相交，每个用户可关联到最近的RSU或中继。我们推导出典型用户的关联概率和覆盖概率，从而能够评估网络性能。此外，我们通过考虑所提网络中不同链路之间的相互作用，研究了用户吞吐量。本文为两层车辆网络的设计提供了实用见解。具体而言，我们将用户关联、用户信干比（SIR）和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佳中继密度和工作带宽，以增强车辆网络的可靠性并最大化用户吞吐量。