Reconfigurable Intelligent Surface Identification in Mobile Networks: Opportunities and Challenges
<|reference_start|>Reconfigurable Intelligent Surface Identification in Mobile Networks: Opportunities and Challenges: The advent of the sixth generation (6G) wireless networks heralds a transformative era for mobile communication, where the integration of cutting-edge technologies like Reconfigurable Intelligent Surfaces (RISs) is paramount in addressing the burgeoning demands for energy efficiency, high data rates, reliable connectivity, and enhanced coverage in densely populated areas. RISs have attracted the attention of academia as well as the industry and emerged as a beacon of innovation, offering a novel paradigm to reconfigure the wireless propagation environment beneficially, thereby enhancing the overall network performance. It is envisioned that the deployment of numerous RISs in a mobile network will serve user equipments (UEs) to boost various key performance indicators (KPIs), with lower energy consumption compared to alternative solutions (e.g., relays, and network-controlled repeaters). However, the knowledge of whether or not a UE is being served through an RIS and if so, which RIS it is being served by is crucial and beneficial for various network planning and operational reasons. In this paper, we address the importance and the benefits of RIS identification in a mobile network. Additionally, we guide the readers and researchers by introducing alternative methods to enable RIS identification. Through the lens of this research, we unveil and shed light to various benefits, the challenges, and future opportunities in the identification of RISs serving mobile users in complex network environments, highlighting the necessity for advanced identification strategies to fully harness the potential of RIS technology in next-generation wireless systems.<|reference_end|>
@article{arslan2024reconfigurable,
    title={Reconfigurable Intelligent Surface Identification in Mobile Networks:
  Opportunities and Challenges},
    author={Emre Arslan, Ali Tugberk Dogukan, Fatih Kilinc, Ahmet Faruk Coskun,
  Ertugrul Basar},
    journal={arXiv preprint arXiv:2407.04731},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.04731},
    primaryClass={eess.SP cs.SY eess.SY}
}