Vehicle-to-everything (V2X) is a core 5G technology. V2X and its enabler, Device-to-Device (D2D), are essential for the Internet of Things (IoT) and the Internet of Vehicles (IoV). V2X enables vehicles to communicate with other vehicles (V2V), networks (V2N), and infrastructure (V2I). While V2X enables ubiquitous vehicular connectivity, the impact of bursty data on the network's overall Quality of Service (QoS), such as when a vehicle accident occurs, is often ignored. In this work, we study both 4G and 5G V2X utilizing Evolved Universal Terrestrial Radio Access New Radio (E-UTRA-NR) and propose the use of socially aware 5G NR Dual Connectivity (en-DC) for traffic differentiation. We also propose localized QoS, wherein high-priority QoS flows traverse 5G road side units (RSUs) and normal-priority QoS flows traverse 4G Base Station (BS). We formulate a max-min fair QoS-aware Non-Orthogonal Multiple Access (NOMA) resource allocation scheme, QoS reclassify. QoS reclassify enables localized QoS and traffic steering to mitigate bursty network traffic's impact on the network's overall QoS. We then solve QoS reclassify via Integer Linear Programming (ILP) and derive its approximation. We demonstrate that both optimal and approximation QoS reclassify resource allocation schemes in our socially aware QoS management methodology outperform socially unaware legacy 4G V2X algorithms (no localized QoS support, no traffic steering) and socially aware 5G V2X (no localized QoS support, yet utilizes traffic steering). Our proposed QoS reclassify scheme's QoS flow end-to-end latency requires only $\approx~15\%$ of the time legacy 4G V2X requires.

翻译：车联网（V2X）是5G核心技术之一。V2X及其使能技术——设备到设备（D2D）——对物联网（IoT）和车联网（IoV）至关重要。V2X使车辆能够与其他车辆（V2V）、网络（V2N）和基础设施（V2I）进行通信。虽然V2X实现了无处不在的车载连接，但突发数据（如车辆事故时产生的数据）对网络整体服务质量（QoS）的影响往往被忽视。本研究基于演进通用陆地无线接入新无线电（E-UTRA-NR）对4G和5G V2X进行了分析，并提出了利用社交感知的5G NR双连接（en-DC）进行流量区分的方法。我们还提出了局部化QoS方案，其中高优先级QoS流通过5G路侧单元（RSU）传输，而普通优先级QoS流则通过4G基站（BS）传输。我们构建了一种最大最小公平的QoS感知非正交多址接入（NOMA）资源分配方案——QoS重分类。QoS重分类通过实现局部化QoS和流量引导来缓解突发网络流量对整体QoS的影响。随后，我们通过整数线性规划（ILP）求解QoS重分类问题并推导其近似解。实验表明，在我们提出的社交感知QoS管理方法中，最优和近似QoS重分类资源分配方案均优于社交非感知的传统4G V2X算法（无局部化QoS支持、无流量引导）和社交感知的5G V2X（无局部化QoS支持但使用流量引导）。我们提出的QoS重分类方案的QoS流端到端延迟仅需传统4G V2X所需时间的约$\approx~15\%$。