Abstract
In recent years, a number of studies have focused on optimizing resource allocation and energy cooperation; however, prior to this time, these two topics were rarely discussed together in the same study. This paper analyzes the topic while keeping in mind both the enormous potential of RE and the difficulties that are associated with resource distribution. We take into consideration the downlink transmission model in millimeter-wave BSs, with each BS being powered by sources of renewable energy (RE), in addition to smart grids, and we optimize for overall system energy efficiency (EE). Within the confines of the constraints imposed by the transmit power of the BSs, the quality of service requirements of the UEs, and the collection energy that is available, an investigation into the problem of resource optimization was carried out with the intention of maximizing the total system energy efficiency (EE) by optimizing user association, power allocation, and energy cooperation. This was done with the intention of maximizing the total system energy efficiency (EE).
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Awan, A.Y., Ali, M., Naeem, M., Qamar, F., Sial, M.N.: Joint network admission control, mode assignment, and power allocation in energy harvesting aided D2D communication. IEEE Trans. Industr. Inf. 16(3), 1914–1923 (2019)
Baidas, M.W., Alsusa, E., Shi, Y.: Resource allocation for SWIPT-enabled energy-harvesting downlink/uplink clustered NOMA networks. Comput. Netw. 182, 107471. https://doi.org/10.1016/j.comnet.2020.107471 (2020)
Basharat, M., Naeem, M., Ejaz, W., Khattak, A.M., Anpalagan, A., Alfandi, O., Kim, H.S.: Non-orthogonal radio resource management for RF energy harvested 5G networks. IEEE Access 7, 46550–46561 (2019)
Cao, Y., Zhong, Y., Peng, X., Pan, S.: Energy efficiency maximization for hybrid-powered 5G networks with energy cooperation. Electronics 11(10), 1605 (2022)
Chughtai, N.A., Ali, M., Qaisar, S., Imran, M., Naeem, M., Qamar, F.: Energy efficient resource allocation for energy harvesting aided H-CRAN. IEEE Access 6, 43990–44001 (2018)
El Hassani, S., El Hassani, H., Boutammachte, N.: Overview on 5G radio frequency energy harvesting. ASTESJ 4, 328–346 (2019)
Hu, S., Chen, X., Ni, W., Wang, X., Hossain, E.: Modeling and analysis of energy harvesting and smart grid-powered wireless communication networks: a contemporary survey. IEEE Trans. Green Commun. Netw. 4(2), 461–496 (2020)
Imran, M., Khan, L.U., Yaqoob, I., Ahmed, E., Qureshi, M.A., Ahmed, A.: Energy harvesting in 5G networks: taxonomy, requirements, challenges, and future directions. arXiv preprint arXiv:1910.00785, 1–9 (2019)
Le, T.D.: Resource allocation in the next generation of wireless networks: vehicular and energy harvesting systems (Doctoral dissertation, École de technologie supérieure). (2022)
Liu, X., Zhang, X., Jia, M., Fan, L., Lu, W., Zhai, X.: 5G-based green broadband communication system design with simultaneous wireless information and power transfer. Phys. Commun. 28, 130–137 (2018)
Natarajan, Y., Kannan, S., Selvaraj, C., Mohanty, S.N.: Forecasting energy generation in large photovoltaic plants using radial belief neural network. Sustain. Comput.: Inf. Syst. 31, 100578 (2021)
Natarajan, Y., Raja, R.A., Kousik, D.N., Johri, P.: Improved energy efficient wireless sensor networks using multicast particle swarm optimization. Available at SSRN 3555764. 1–6. https://doi.org/10.1016/j.suscom.2021.100578 (2020)
Okundamiya, M.S., Wara, S.T., Obakhena, H.I.: Optimization and techno-economic analysis of a mixed power system for sustainable operation of cellular sites in 5G era. Int. J. Hydrogen Energy 47(39), 17351–17366 (2022)
Omar, N.: Energy harvesting in fifth generation 5G wireless communications. Halaman 26–31, JUADAH MINDA (2018)
Ozger, M., Cetinkaya, O., Akan, O.B.: Energy harvesting cognitive radio networking for IoT-enabled smart grid. Mobile Netw. Appl. 23(4), 956–966 (2018)
Pan, Q., Wu, J., Zheng, X., Yang, W., Li, J.: Differential privacy and IRS empowered intelligent energy harvesting for 6G internet of things. IEEE Internet Things J. 9(22), 22109–22122 (2021)
Pang, L., Zhao, H., Zhang, Y., Chen, Y., Lu, Z., Wang, A., Li, J.: Energy-efficient resource optimization for hybrid energy harvesting massive MIMO systems. IEEE Syst. J. 16(1), 1616–1626 (2021)
Rajaram, A., Khan, R., Tharranetharan, S., Jayakody, D.N.K., Dinis, R., Panic, S.: Novel SWIPT schemes for 5G wireless networks. Sensors 19(5), 1169 (2019)
Syed, S.A., Sheela Sobana Rani, K., Mohammad, G.B., Chennam, K.K., Jaikumar, R., Natarajan, Y., Sundramurthy, V.P.: Design of resources allocation in 6G cybertwin technology using the fuzzy neuro model in healthcare systems. J. Healthc. Eng. (2022). https://doi.org/10.1155/2022/5691203
Wang, K.: Energy-efficient resource allocation optimization algorithm in industrial IoTs scenarios based on energy harvesting. Sustain. Energy Technol. Assess. 45, 101201 (2021)
Wang, Z.L., Wu, W.: Nanotechnology-enabled energy harvesting for self-powered micro-/nanosystems. Angew. Chem. Int. Ed. 51(47), 11700–11721 (2012)
Wang, X., Ning, Z., Hu, X., Wang, L., Guo, L., Hu, B., Wu, X.: Future communications and energy management in the Internet of vehicles: toward intelligent energy-harvesting. IEEE Wirel. Commun. 26(6), 87–93 (2019)
Yuvaraj, N., Raja, R.A., Ganesan, V., Dhas, C.S.G.: Analysis on improving the response time with PIDSARSA-RAL in ClowdFlows mining platform. EAI Endorsed Trans. Energy Web 5(20), e2–e2 (2018)
Yuvaraj, N., Raja, R.A., Karthikeyan, T., Kousik, N.V.: Improved privacy preservation framework for cloud-based internet of things. In: Internet of things, pp. 165–174. CRC Press, (2020)
Zhang, J., Lou, M., Xiang, L., Hu, L.: Power cognition: Enabling intelligent energy harvesting and resource allocation for solar-powered UAVs. Futur. Gener. Comput. Syst. 110, 658–664 (2020)
Acknowledgements
The work was supported by Researchers Supporting Project number (RSP2023R492), King Saud University, Riyadh, Saudi Arabia.
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NCK: Investigation, Methodology, Writing—review & editing. SS: Conceptualization, Formal analysis, Writing—review & editing. GS: Conceptualization, Formal analysis, Writing—original draft Writing—review & editing. NS: Conceptualization,, Writing—review & editing. AG: Writing—review & editing. EAA: Formal analysis, Writing—review & editing. AI: Formal analysis, Writing—review & editing.
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Kiran, N.C., Senthilkumar, S., Satish, G. et al. Solar energy harvesting to optimise the power constraints in 5G systems. Opt Quant Electron 55, 1251 (2023). https://doi.org/10.1007/s11082-023-05488-z
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DOI: https://doi.org/10.1007/s11082-023-05488-z