Channel Coding QoS Analysis in 5G V2X Dynamic Propagation Models

Vehicle-to-everything (V2X) communications is a crucial area of wireless communications and is of primary interest for automakers, smart cities, municipal services, traffic planners, and law enforcement authorities. V2X systems are beneficial for increasing driving safety, driving time, the ability to avoid accidents, traffic congestion and energy saving. However, the V2X communication is not only characterized by high mobility and but also by rapid and unexpected changes in the communication environment, which drastically degrade the fading features and the quality of the communication channel. Maintaining tolerable quality of service (QoS) in a V2X communication environment is therefore essential. Thus, under the premise of ensuring channel quality, channel coding is employed as the predominant process enhancing reliability by introducing high data redundancy. In this study, we investigate the impact of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5th-Generation New Radio (5G-NR) polar codes, and 5G-NR low-density parity-check (LDPC) codes on the QoS of a V2X communication system. To this end, we propose space and time-varying V2X propagation models, based on real traffic data, that simulate V2X communication in real urban and highway environments and various traffic density conditions, based on the 3rd-Generation Partnership Project (3GPP) specifications. Through these simulations we investigate the frame error rate (FER) performance and QoS efficiency of the V2X dynamic propagation models which are achieved by the 4G-LTE and 5G-NR channel coding schemes. Our analysis introduces novel large-scale V2X fading models and ultimately proves that turbo-based coding schemes have superior performance for small-frame 5G V2X communication.