# A Preemptive-Resume Priority MAC Protocol for Efficient BSM Transmission in UAV-Assisted VANETs
## 2 Related Works  
Regarding UAV-assisted VANETs, a model was introduced in [18] to estimate the probability of line-of-sight propagation in air-to-ground wireless communication across different urban environments. This model integrates building distribution, terrain, and other environmental parameters while accounting for signal attenuation, scattering, and multipath propagation. In [19], the authors put forward an aerial-to-ground path loss model based on the probability model of LOS using UAVs. They further provided a methodology for determining the optimal height and angle of the UAV based on this model. Moreover, Ref. [20] introduced the integration of UAV assistance to enhance the connectivity and support services in urban vehicle VANETs. By leveraging UAVs as mobile base stations, communication among vehicles can be enhanced, thereby facilitating the provision of additional services. In [21], the authors introduced a routing approach that leverages UAVs for connectivity and traffic density perception. By employing UAVs as relay nodes, the Connected and Reliable UAV-assisted Vehicular (CRUV) network can dynamically select the most suitable routing path, thereby improving the efficiency and reliability of data transmission within vehicular self-organizing networks. Ref. [22] introduces a methodology that leverages UAVs to provide services for highway VANETs and distributed antenna systems. Through the deployment of UAVs, the communication quality between vehicles can be enhanced, resulting in wider network coverage and stronger signal gain. Ref. [23] introduces a traffic service solution aimed at minimizing latency in multi-tier UAV networks. By taking into account the hierarchical structure, connectivity, and data transmission demands of the UAV network, this scheme optimizes traffic routing and scheduling strategies to effectively reduce latency and ensure the provision of reliable traffic services. There are currently two methods available to tackle the congestion traffic control problem in BSM transmission. The first approach involves regulating the BSM generation frequency. In [24], the LIMERIC algorithm is proposed, which actively monitors the real-time congestion status of the network and dynamically adjusts the message rate according to the prevailing network conditions. This algorithm demonstrates notable improvements in system throughput and latency reduction, thereby better satisfying the communication demands of the Dedicated Short-Range Communications (DSRC) system. Ref. [25] presents a congestion control technique that utilizes power or rate adaptation. By dynamically adjusting the transmission power or transfer rate of vehicle nodes in response to the prevailing network congestion level, this approach endeavors to optimize the utilization of network resources and mitigate congestion. In [26], the authors propose a distributed algorithm design approach called DRCV, which leverages collaboration and information exchange among vehicle nodes to achieve efficient utilization of network resources and congestion control. The second approach to tackle congestion traffic control issues in BSM transmission involves power control, which regulates the transmission power of BSM. However, due to the influence of interference and path loss among vehicle nodes, distributed power control algorithms may experience anomalies during practical implementations [27]. To overcome these challenges, the authors proposed an enhanced algorithm that leverages signal strength measurement and collaboration among vehicle nodes. By dynamically adjusting the transmission power of nodes, this algorithm endeavors to improve system performance and mitigate interference. Ref. [28] presents a novel approach that involves real-time monitoring and analysis of vehicle status and the communication environment. This method enables the dynamic adjustment of communication parameters and route selection to optimize the overall communication performance.