Optimising Video Transmission Performance in 5G New Radio Technology for Vehicle-to-Network (V2N) Application: A Comprehensive Analysis

• Published in: 2023 11th International Conference on Information and Communication Technology, ICoICT 2023
• Main Author: Khalid S.; Abidin H.Z.; Mazalan L.; Abdullah S.A.C.
• Format: Conference paper
• Language: English
• Published: 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174417698&doi=10.1109%2fICoICT58202.2023.10262660&partnerID=40&md5=bbbe27c1c51f2232e2b17e82b2a0c727

With the increasing demand for efficient and reliable communication in the transportation industry, the Vehicle-to-Network (V2N) application leveraging 5G New Radio (NR) technology has gained significant attention. Video transmission plays a critical role in V2N communication, enabling real-time information exchange between vehicles and the network infrastructure. However, the performance of video transmission in this context is influenced by various factors such as latency, bandwidth, reliability, and scalability. This paper presents a comprehensive performance analysis of video transmission on 5G NR technology for V2N application. The analysis focuses on addressing key issues, in particular the latency, and throughput of uplink data transmission. A set of experiments were conducted in a simulated urban environment on OMNET++ simulator using Simu5G framework. The results reveal that while all algorithms show similar trends in average MAC throughput, the MAX C/I algorithm outperforms the others at higher loads, achieving up to 14.5% higher throughput. In terms of delay, the PF algorithm exhibits the lowest average MAC delay, reducing delay time by up to 17.5%. Conversely, the DRR algorithm shows the highest delay, with a cumulative delay reaching 25.7% higher than the other algorithms. These findings offer valuable insights for optimizing resource allocation and improving network efficiency in 5G deployments. Future research can focus on enhancing delay performance, exploring fairness-delay trade-offs, and assessing scalability in larger networks. © 2023 IEEE.