Intelligent Reflecting Surfaces (IRS) have emerged as a groundbreaking technology to revolutionize the landscape of Vehicle-to-Everything (V2X) communication systems. V2X communication plays a pivotal role in the development of safe, efficient, and autonomous transportation. However, it faces significant challenges in terms of signal propagation, interference, and connectivity. IRS offers an innovative solution by actively controlling radio waves to optimize wireless communication links in V2X scenarios. Intelligent Reflecting Surfaces are increasingly essential in Vehicle-to-Everything communication due to their capacity to address critical challenges in this domain. IRS technology enhances connectivity by extending communication range, mitigating interference, and reducing latency, thereby ensuring that V2X systems can reliably transmit vital information for autonomous vehicles, advanced driver assistance systems, and traffic management. In this work, investigation of IRS assisted V2X communication is done, while enabling efficient spectrum utilization, enhanced data rate, and improved coverage in terms of simulation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intelligent Reflecting Surface assisted V2X Communication


    Contributors:


    Publication date :

    2024-05-03


    Size :

    484143 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    An Overview of Intelligent Reflecting Surface Assisted UAV Communication Systems

    Sur, Samarendra Nath / Kandar, Debdatta / Imoize, Agbotiname Lucky et al. | Springer Verlag | 2022



    Imperfect CSI Based Design for Intelligent Reflecting Surface Assisted MISO Systems

    Chen, Hongchao / Xu, Simeng / Wang, Jiajia et al. | IEEE | 2022


    Throughput Optimization of Intelligent Reflecting Surface Assisted User Cooperation in WPCNs

    Zheng, Yuan / Bi, Suzhi / Zhang, Ying-Jun Angela et al. | IEEE | 2020