Assessing electromagnetic field exposure levels in multi-active reconfigurable intelligent surface assisted 5G network

Citation

Ahmed Salem, Mohammed and Lim, Heng Siong and Chua, Ming Yam and Alaghbari, Khaled Abdulaziz and Zarakovitis, Charilaos C. and Chien, Su Fong (2024) Assessing electromagnetic field exposure levels in multi-active reconfigurable intelligent surface assisted 5G network. International Journal of Electrical and Computer Engineering (IJECE), 14 (4). p. 4110. ISSN 2088-8708

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Assessing electromagnetic field exposure levels in multi-active reconfigurable intelligent surface assisted 5G network _ Ahmed Salem _ International Journal of Electrical and Computer Engineering (IJECE).pdf - Published Version
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Abstract

As 5G mobile networks continue to proliferate in dense urban environments, it becomes increasingly important to understand and mitigate excessive electromagnetic field (EMF) exposure. This study investigates how the downlink EMF exposure levels of 5G millimeterwave (mm-wave) mobile networks are influenced by the integration of multi-active reconfigurable intelligent surfaces (RISs), using a ray-tracing approach. Our research employs a comprehensive two-step methodology: Firstly, we introduce a new RIS-assisted 5G mm-wave network planning technique. This technique leverages a machine learning (ML) approach for the classification of multi-RIS clusters. The primary goal is to optimize coverage while minimizing the number of required RIS deployments. This is achieved by strategically placing RISs based on the ML classification, ultimately aiming to enhance network efficiency. Secondly, we conducteda thorough comparative analysis, evaluating the impact of both passive and active RISs on EMF exposure level throughout a dense urban environment. Passive RISand active RIS differ in their adaptability to changing network conditions. The result shows that the influence of multi-active RISs on EMF exposure is significant (about 7.5 times higher) compared to passive RISs

Item Type: Article
Uncontrolled Keywords: 5G mobile networks
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 02 Jul 2024 03:09
Last Modified: 02 Jul 2024 03:09
URII: http://shdl.mmu.edu.my/id/eprint/12545

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