Abstract
This paper presents a promising solution for enhancing the reliability and data rate of Internet-of-vehicles (IoV) visible light communication (VLC) systems through the utilization of optical reconfigurable intelligent surfaces (RISs). The focus is on the infrastructure-to-vehicle (I2V) scenario, where streetlights serve as internet access points. The IoV-VLC system is modeled using an advanced non-sequential raytracing approach. A novel closed-form channel model expression is proposed, incorporating transceiver, RIS, and infrastructure parameters. The proposed model is then validated against broadband raytracing simulation results considering different combinations of system parameters, including, receiver aperture size, streetlight pole height, spacing between the poles, and RIS height. Moreover, based on the derived channel model, the error rate and data rate performances of the system are analyzed. The required numbers of RIS elements allocated to each vehicle's location, to achieve a target error rate and data rate values, are further derived. Finally, this paper demonstrates the impact of various transceiver, RIS, and infrastructure parameters on the system performance. The obtained results reveal that the proposed IoV-VLC system with optimal RIS deployment effectively addresses system outage issues and meets reliability and data speed requirements regardless of the vehicle's location. The results also shed light on the influence of various factors on system performance. Notably, the total number of required RIS elements is significantly affected by factors such as receiver aperture size, space between the poles, and transmit power budget. For instance, when considering the same power budget and error rate target, the required number of RIS elements for spacing distances of 20 m, 22 m, and 24 m are determined as 132, 244, and 428 elements, respectively. Conversely, the impact of pole height is found to be minimal as long as the space between the poles remains fixed and within the prescribed regulations.
| Original language | British English |
|---|---|
| Journal | IEEE Transactions on Vehicular Technology |
| DOIs | |
| State | Accepted/In press - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Channel modeling
- Internet-of-vehicles
- reconfigurable intelligent surfaces
- visible light communication
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