@article{Yang2026, 
author = {Ruihang Yang and Li Wei and Dezhi Wang and Bingzhe Du and Chen Zhu and Kai Wang and Zhengyu Zhu and Xiaoming Chen and Zhaohui Yang and Chongwen Huang},
title = {RIS-Assisted Vehicular ISAC: A Robust Sensing-Centric System Design},
year = {2026},
journal = {Tsinghua Science and Technology},
keywords = {Integrated sensing and communication, reconfigurable intelligent surface, vehicular networks,  sensing-centric design},
url = {https://www.sciopen.com/article/10.26599/TST.2026.90100033},
doi = {10.26599/TST.2026.90100033},
abstract = {The convergence of sensing and communication, termed integrated sensing and communication (ISAC), is a cornerstone technology for next-generation autonomous vehicular networks. However, the performance of these systems is frequently constrained by harsh propagation environments featuring blockages. Reconfigurable intelligent surface (RIS) has emerged as a potent technique for intelligently tailoring the propagation environment, thereby yielding significant benefits for vehicular ISAC. This paper proposes a novel beamforming scheme integrating passive beamforming at RIS and active beamforming at vehicular ends. Efficient solutions to the formulated optimization problem are subsequently derived via alternating optimization (AO) and semidefinite relaxation (SDR) methods. Two practical criteria are employed for solving the optimization problem: one is fairness-oriented, i.e., ensuring uniform coverage, denoted as Max-Min-SNR; the other focuses on maximizing total information, termed Max-SIR. Simulation results show that, compared with existing baseline schemes, the Max-Min-SNR-based beamforming scheme attains a 7.66 dB (5.8-fold) enhancement in the minimum sensing SNR, while the Max-SIR-based scheme delivers a 45% information rate gain—thus verifying the superiority of the proposed beamforming scheme.}
}