Document Type
Article
Publication Title
IEEE Internet of Things Journal
Abstract
Internet-of-vehicles (IoV) is an emerging paradigm with significant potential to improve traffic efficiency and driving safety. Here, we focus on the design of a novel visible light communication (VLC)-assisted scheme to enable driving safety-related IoV services that require ultra-reliable and low-latency communications (URLLC). Specifically, the vehicle-to-vehicle (V2V) communication mode is adopted to satisfy the ultra-low latency requirement of URLLC in roadside infrastructure-less IoV systems. In the outdoor V2V-VLC scenarios, the quality of the received optical signal is degraded by path loss, atmospheric turbulence and additive noise. In addition, the short-packet feature of URLLC introduces inevitable data decoding errors and imperfect channel state information (CSI). With this background, we aim to investigate the reliability performance of URLLC in outdoor V2V-VLC systems, which is described by the average packet loss probability under given user-plane transmission latency. First, we consider the ideal case of a perfect CSI at the receiver, and derive an analytical expression of average packet loss probability. Further, a closed-form approximation is provided to simplify the numerical calculation. Next, we extend the theoretical analysis to a practical V2V-VLC system with imperfect CSI at the receiver. Through numerical results, we validate the accuracy of our designed theoretical framework and propose ideas to enable driving safety-related IoV services in outdoor V2V-VLC systems.
First Page
8185
Last Page
8198
DOI
10.1109/JIOT.2023.3321268
Publication Date
10-2-2023
Keywords
Ultra reliable low latency communication, Reliability, Optical receivers, Adaptive optics, Visible light communication, Internet of Things, Vehicular ad hoc networks, IoV, URLLC
Recommended Citation
Y. Xie, D. Xu, T. Zhang, K. Yu, A. Hussain and M. Guizani, "VLC-Assisted Safety Message Dissemination in Roadside Infrastructure-Less IoV Systems: Modeling and Analysis," in IEEE Internet of Things Journal, vol. 11, no. 5, pp. 8185-8198, 1 March1, 2024, doi: 10.1109/JIOT.2023.3321268.
Comments
Preprint version from Essex University repository
Uploaded on June 11, 2024