INVESTIGATORY ANALYSIS OF ENERGY REQUIREMENT OF A MULTI-TENANT MOBILE COMMUNICATION BASE STATION
Published 2025-03-19
Keywords
- Energy Efficiency,
- Mobile Network Sustainability,
- Multi-tenant Base Station,
- Power Consumption, Solar Power System.
How to Cite
Copyright (c) 2025 Academic Journal of Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
Energy consumption in mobile communication base stations (BTS) significantly impacts operational costs and the environmental footprint of mobile networks. This study examines the energy requirements of a multi-tenant BTS, focusing on power consumption patterns, key energy-intensive components, and optimization strategies. Empirical measurements under varying load conditions revealed that power consumption is network load-dependent and time-dependent, with peak demand occurring between 9:30 AM – 2:30 PM and 7:30 PM – 11:30 PM. The multi-tenant BTS required approximately 7.67 kW, compared to 2.5 kW for a single-tenant BTS. Additionally, the annual cost of diesel for generator power was estimated at ₦17,712,000, emphasizing the financial strain of conventional energy sources. A standalone solar power system is recommended as a sustainable alternative, designed to meet the identified power demands. A multi-tenant BTS model is also presented as a test-bed for designing and simulating a suitable solar power system. Power amplifiers and cooling systems were identified as the most energy-intensive components. Implementing dynamic load management and renewable energy solutions can significantly reduce energy demand, enhance efficiency, and lower operational costs. This study offers practical recommendations for optimizing energy use in multi-tenant BTS operations, supporting cost-effective, reliable, and sustainable mobile network infrastructure
References
- Abonyi, D., & Rigelsford, D. (2018). A system for optimizing small-cell deployment in 2-tier HetNets. 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 1–6. https://doi.org/10.1109/CAMAD.2018.8514981
- Ahmed, S., Li, W., & Zhao, T. (2022). Renewable energy integration for green mobile networks: A comprehensive review. Renewable Energy Journal, 58(3), 122–137. https://doi.org/10.1016/j.renene.2022.01.003
- Buzzi, S., Poor, H. V., & Zappone, A. (2021). Energy-efficient strategies for 5G multi-tenant networks. IEEE Transactions on Communications, 69(4), 2356–2370. https://doi.org/10.1109/TCOMM.2021.3052301
- Hasan, Z., Boostanimehr, H., & Bhargava, V. K. (2021). Energy-efficient cellular networks: A survey of research challenges and solutions. IEEE Communications Surveys & Tutorials, 23(1), 524–540. https://doi.org/10.1109/COMST.2021.3012311
- Kumar, R., Singh, D., & Gupta, P. (2021). Advanced cooling systems for energy-efficient mobile base stations. Energy Efficiency Journal, 14(2), 78–92. https://doi.org/10.1007/s12053-021-09928-3
- Li, Y., Xu, S., & Wu, Z. (2020). Multi-tenant base stations: Opportunities and challenges in energy management. IEEE Wireless Communications, 27(2), 8–14. https://doi.org/10.1109/WC.2020.8962123
- United Nations. (2023). Sustainable development goals. United Nations. https://sdgs.un.org
- Zhao, Y., Tang, J., & Blume, O. (2023). Dynamic power allocation for energy-efficient multi-tenant base stations. IEEE Transactions on Wireless Communications, 22(4), 1095–1107. https://doi.org/10.1109/TWC.2023.3014520
