Smart Mirrors on the Road: Eliminating Dead Zones in Vehicular Light-Based Networks
#Communication
#Visible
#Light
In our increasingly connected cities, vehicular communication is key for safety and efficiency. However, in multicell Visible Light Communication (VLC) systems, a critical fairness issue arises: vehicles at the edge of a communication cell experience drastically slower data rates due to weak signals and interference from adjacent cells. This digital "slow lane" compromises the reliability of the entire network.
This presentation introduces a novel cooperative transmission framework that addresses this challenge head-on. By integrating Optical Intelligent Reflecting Surfaces (OIRS) - essentially smart mirrors for light - we can create new, robust communication pathways and intelligently mitigate inter-cell interference. We will explore how this architecture transforms the network from a collection of isolated cells into a collaborative system. The core of this work is a resource allocation problem formulated to maximize the minimum data rate for any vehicle in the system, a concept known as max-min fairness. I will walk through the proposed algorithm, which efficiently solves this complex problem by decomposing it into three manageable subproblems: OIRS assignment, subchannel allocation, and power adjustment. These are solved iteratively using a block coordinate descent method.
Through simulation results, we will see that this cooperative OIRS-assisted approach significantly outperforms existing baseline methods. The findings confirm a substantial improvement in max-min fairness, ensuring more consistent and reliable connectivity for all vehicles, regardless of their position. This work is a crucial step toward deploying fair and efficient vehicular VLC systems, paving the way for the next generation of intelligent transportation networks.
This presentation is based on the paper:
"Resource Allocation for Fairness Enhancement in Multicell Vehicular VLC System With Optical IRS: A Cooperative Transmission Approach," by N. An, F. Yang, C. Liu, L. Cheng, J. Song, and Z. Han, published in the IEEE Internet of Things Journal, vol. 12, no. 11, pp. 16931-16946, June 2025.
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Ling Cheng
Topic:
Smart Mirrors on the Road: Eliminating Dead Zones in Vehicular Light-Based Networks
In our increasingly connected cities, vehicular communication is key for safety and efficiency. However, in multicell Visible Light Communication (VLC) systems, a critical fairness issue arises: vehicles at the edge of a communication cell experience drastically slower data rates due to weak signals and interference from adjacent cells. This digital "slow lane" compromises the reliability of the entire network.
This presentation introduces a novel cooperative transmission framework that addresses this challenge head-on. By integrating Optical Intelligent Reflecting Surfaces (OIRS) - essentially smart mirrors for light - we can create new, robust communication pathways and intelligently mitigate inter-cell interference. We will explore how this architecture transforms the network from a collection of isolated cells into a collaborative system.
The core of this work is a resource allocation problem formulated to maximize the minimum data rate for any vehicle in the system, a concept known as max-min fairness. I will walk through the proposed algorithm, which efficiently solves this complex problem by decomposing it into three manageable subproblems: OIRS assignment, subchannel allocation, and power adjustment. These are solved iteratively using a block coordinate descent method.
Through simulation results, we will see that this cooperative OIRS-assisted approach significantly outperforms existing baseline methods. The findings confirm a substantial improvement in max-min fairness, ensuring more consistent and reliable connectivity for all vehicles, regardless of their position. This work is a crucial step toward deploying fair and efficient vehicular VLC systems, paving the way for the next generation of intelligent transportation networks.
This presentation is based on the paper:
"Resource Allocation for Fairness Enhancement in Multicell Vehicular VLC System With Optical IRS: A Cooperative Transmission Approach," by N. An, F. Yang, C. Liu, L. Cheng, J. Song, and Z. Han, published in the IEEE Internet of Things Journal, vol. 12, no. 11, pp. 16931-16946, June 2025.
Biography:
LING CHENG, SMIEEE: received the degree B. Eng. Electronics and Information (cum laude) from Huazhong University of Science and Technology (HUST) in 1995, M. Ing. Electrical and Electronics (cum laude) in 2005, and D. Ing. Electrical and Electronics in 2011 from University of Johannesburg (UJ). His research interests are in Telecommunications, Renewable Energy and Artificial Intelligence. In 2010, he joined University of the Witwatersrand where he was promoted to Full Professor in 2019. He serves as the associate editor of three journals. He has published more than 150 research papers in journals and conference proceedings. He has been a visiting professor at five universities and the principal advisor for over forty full research post-graduate students to completion including 12 PhDs. He was awarded the Chancellor’s medals in 2005, 2019 and the National Research Foundation ratings in 2014, 2020 and 2025. The IEEE ISPLC 2015 best student paper award was made to his Ph.D. student in Austin. He is a senior member of IEEE and the vice-chair of IEEE South African Information Theory Chapter.
