Enhancements of Digital Twinning in Reducing the Carbon Footprint of Mobile Communication Networks

Reducing energy consumption in mobile network components is crucial to minimize operational costs and support sustainable telecommunication practices in the 5G networks industry. In this paper, we argue that Digital Twin technology can improve all phases of the new intelligent networks' workflow and how it could be a powerful tool to fulfill the potential of 5G networks and beyond, due to its adaptability and scalability properties that allow it to integrate new AI/ML algorithms faster, more scalable, and more precisely. The implementation of sensors enables the construction of visualized models for mobile network elements, providing real-time data from the physical infrastructure to optimize energy usage, implement predictive maintenance, enhance network reliability, and monitor network performance seamlessly. By leveraging these advanced models, operators can achieve proactive decision-making, minimize energy waste, and streamline network upgrades while effectively addressing modern mobile communication systems' dynamic energy demands.