Energy-Efficient Resource Allocation For Ultra-Dense 5G Mobile Networks


Salem, Mohammed Ahmed and Lim, Heng Siong and Chua, Ming Yam (2021) Energy-Efficient Resource Allocation For Ultra-Dense 5G Mobile Networks. In: 2nd FET PG Engineering Colloquium Proceedings 2021, 1-15 Dec. 2021, Online Conference. (Unpublished)

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To provide higher data rate and more reliable mobile services, the forthcoming 5G system is expected to densify its network infrastructure substantially and deploy massive antenna arrays that emit high-energy beams. These trends raise tangible concerns to scientists and citizens about the adverse effects of such networks on public safety and health. The existing mobile networks are designed for optimizing spectral-efficiency (SE) and energy-efficiency (EE) only. To better protect the public from excessive radiation, new constraints must be introduced in the resource allocation algorithms of the ultra-dense 5G networks so that the available radio resources can be allocated more effectively than in legacy systems while limiting the user exposure to EMF radiation. Some initial works in this direction have been done recently, which however, are limited to 4G networks with narrower exposure scenarios compared to 5G networks. Moreover, The EMF exposure due to a practical beamforming technique such as hybrid beamforming has not been adequately investigated in the literature. Furthermore, the existing research regarding beamforming weights (digital and analogue) design did not consider any radiation awareness constraints. This project aims to address these research gaps by proposing a radiation-aware radio resource scheduling algorithm that jointly optimizes the SE and EE requirements of the 5G networks while limiting the user EMF exposure levels below the official safety standards. There are two phases of work in this project: In phase 1, EMF exposure for 5G mobile networks in dense urban indoor and outdoor environments considering beamforming techniques and intelligent reflecting surface (IRS) will be investigated using ray-tracing simulation approach; In phase 2, new radiation-aware energy-efficient resource allocation algorithms for hybrid beamforming technique will be developed for 5G mobile networks using advanced constrained optimization approach. Extensive computer simulation will be conducted for evaluating the performance of the proposed method in realistic scenarios. The outcome of this work will contribute towards a safer, better, and greener 5G service for the sake of the well-being of our communities.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Spectral-efficiency (SE), energy-efficiency (EE), hybrid beamforming, intelligent reflecting surface (IRS), resource allocation
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: 26 Jan 2022 01:48
Last Modified: 26 Jan 2022 01:48


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