Cost-Effective Power Management for Green Mobile Base Stations
Power consumption in mobile communication networks constitutes 20-40% of the operating expenditure. The energy footprint is especially high at the radio access network (RAN), where Base stations (BSs) account for 60-80% of network power usage. In this context, we propose in this paper a novel power coordination framework that efficiently utilizes multiple power sources including conventional grid power, renewable energy, and battery storage systems. The proposed model incorporates dynamic pricing schemes and considers environmental impact while maintaining operational cost efficiency. Using Mixed Integer Linear Programming (MILP), we develop a scheduling framework that optimizes when to charge batteries and utilize renewable energy sources for either BS operation or battery charging, aiming to reduce energy consumption costs. Our simulation results demonstrate that the proposed solution achieves significant cost reduction compared to traditional greedy power consumption methods while maintaining service quality. Moreover, it outperforms purely renewable energy-based solutions which, while cost-effective, suffer from service interruptions with a Mean Time Between Failures (MTBF) of 10 minutes. Also, our proposed solution achieves superior performance than heuristic methods, by obtaining optimal results in 2 seconds compared to 5 minutes for heuristic approaches. This work contributes to the development of more sustainable and economically viable mobile network operations without penalizing service quality.
Authors
- Rami Langar (ORCID: https://orcid.org/0000-0002-4674-6700)
- Joseph Antoun (ORCID: https://orcid.org/0000-0002-5638-5734)
- Wael Jaafar (ORCID: https://orcid.org/0000-0003-4378-9999)
Institutions
- École de Technologie Supérieure (CA)
Publication Details
- Published
- 2025-06-08
- DOI
- https://doi.org/10.1109/icc52391.2025.11161696
- Primary Topic
- Internet of Things and Social Network Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00