# 5G-MEC Testbeds for V2X Applications
## 1 Introduction  
Fifth-generation (5G) mobile networks define three usage scenarios: Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine-Type Communication (mMTC) [1]. Among these, URLLC represents an enabler of advanced automotive applications. The stringent latency requirements of these applications triggered research activities aimed at moving the network's core computational resources to the network's edge. Due to the shorter physical distance, edge computing resources can minimize latency, allowing for real-time services. Information or real-time data can be processed at the network's edge using computational resources and a large amount of data are sent to a data center. The delivery of Machine Learning (ML) and Artificial Intelligence (AI) applications from the cloud to edge devices, or even to the sensors themselves, is one of the challenges of edge computing [2]. The difficulty is handling data reliably and effectively in contexts with limited computational and storage resources. There have been several discussions and developments regarding standards in edge computing. The European Telecommunications Standards Institute (ETSI) is one notable organization in this regard. The ETSI defines and standardizes Multi-Access Edge Computing (MEC) technology. According to the 5G Automotive Association (5 GAA), MEC is one of the essential enabling technologies for many of the anticipated services and applications for connected cars and self-driving [3]. The automobile sector needs MEC to deal with the exponential explosion of data in autonomous vehicles. As automobiles create a high amount of data daily, ways to efficiently process all the sensor data in the car and upload some of that data to the cloud are becoming significant difficulties. Furthermore, safety-related features must be available and we cannot rely on wireless connectivity. MEC can meet the stringent requirements of URLLC applications and ensure Quality of Service (QoS) by deliveringMEC services to application developers and content suppliers. MEC allows operators to access the cloud infrastructure, regardless of the underlying Radio Access Network (RAN) (e.g., Third-Generation Partnership Project (3 GPP) [4]). MEC's agnostic nature makes deployments effortless. Vehicle-to-Everything (V2X) applications benefit from both 5G and MEC [5]. Vehicles can connect with the Road-Side Unit (RSU) infrastructure and other vehicles around them using this technology. The vehicle communicates with compatible equipment via a short-range wireless signal that is immune to interference and bad weather. V2X technologies are primarily employed to improve safety and avoid collisions. Vehicle-to-Infrastructure (V2I), Vehicle-to-Network (V2N), Vehicle-to-Pedestrian (V2P), Vehicle-to-Device (V2D), Vehicle-to-Grid (V2G), and Vehicle-to-Vehicle (V2V) are the primary types of V2X technology [6]. V2I technology gives real-time infrastructure data to drivers, including road conditions, traffic congestion, parking availability, and accidents. V2V communication allows cars to transmit messages to each other via a wireless network about what they are doing, including their speed, position, braking, direction of motion, and loss of stability. Dedicated Short-Range Communications (DSRC) technology is enabled, which is equivalent to Wi-Fi [7]. Almost all road safety services and most traffic management and efficiency services require the periodic transmission of V2V and V2I messages with extremely low latency and high reliability [8]. The performance of V2X applications depends on many parameters at different layers of the protocol stack, from the physical problems related to the 5G radio link conditions to networking issues related to the QoS guarantee of the exchanged data and application problems related to the storage and computational resources available for completing application tasks.