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 article, 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 shed light on various benefits for, the challenges to, 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.

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Publication Details

Journal
IEEE Wireless Communications
Published
2025-04-21
DOI
https://doi.org/10.1109/mwc.002.2400228
Citations
4
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
2.85
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article

Reconfigurable Intelligent Surface Identification in Mobile Networks: Opportunities and Challenges

Ahmet F. Coskun, Ertuğrul Başar, Fatih Kılınç, Ali Tuğberk Doğukan et al.
4 citations
IEEE Wireless Communications
Modular Robots and Swarm Intelligence
2.85
article

Reconfigurable Intelligent Surface Identification in Mobile Networks: Opportunities and Challenges

Ahmet F. Coskun, Ertuğrul Başar, Fatih Kılınç, Ali Tuğberk Doğukan, Emre Arslan
article en
4 citations

Abstract

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 article, 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 shed light on various benefits for, the challenges to, 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.

IEEE Wireless CommunicationsVol. 32(4)
Koç University (TR), Ultra Communications (United States) (US), Turkcell (Turkey) (TR)
Openalex Percentile: Top 10%
Modular Robots and Swarm Intelligence
2.85
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