In this work, we explore the use of active reconfigurable intelligent surfaces (A-RIS) to improve vehicle-to-everything (V2X) communication systems to address limitations in traditional vehicular communication. In particular, we formulate an optimization problem to maximize the uplink sum rate for vehicle-to-infrastructure (V2I) links by optimizing transmit precoders, phase-shift matrices, transmit power, and spectrum sharing for vehicle-to-vehicle (V2V) links. To handle complex hybrid control scenarios, we propose a mixed-action deep reinforcement learning (DRL) algorithm and compare it with conventional benchmark methods like deep deterministic policy gradient (DDPG) with discrete actions (DA) and alternating optimization (AO). We evaluate the proposed algorithm’s effectiveness under imperfect channel state information as well. Simulation results highlight the efficacy of our approach, demonstrating significant enhancement in vehicular communication quality through A-RIS. Furthermore, we illustrate the impact of various factors such as number of A-RIS elements, vehicle speed, loss, execution time, amplification power, and CSI error on the performance of the V2X system.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Enhancing V2X Communication with Active RIS: A MADRL Approach with Perfect and Imperfect CSI


    Beteiligte:
    Saikia, Prajwalita (Autor:in) / Singh, Keshav (Autor:in) / Huang, Wan Jen (Autor:in) / Bazzi, Wael (Autor:in) / Biswas, Sudip (Autor:in)


    Erscheinungsdatum :

    07.10.2024


    Format / Umfang :

    613543 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    MADRL-based UAVs Trajectory Design with Anti-Collision Mechanism in Vehicular Networks

    Spampinato, Leonardo / Testi, Enrico / Buratti, Chiara et al. | ArXiv | 2024

    Freier Zugriff

    Cooperative Maneuvering Decision-Making of Multi-UAVs Based on MADRL-VD

    Li, Haolin / Guo, Zhengyu / Lin, Longbin et al. | Springer Verlag | 2024


    MADRL-based UAV swarm non-cooperative game under incomplete information

    WANG, Ershen / LIU, Fan / HONG, Chen et al. | Elsevier | 2024

    Freier Zugriff


    Evaluation of Perfect and Imperfect-Gas Interferograms by Computer

    G. Ben-Dor / B. T. Whitten / I. I. Glass | NTIS | 1979