Energy Modelling of Mobile Network Components

The substantial rise in global data traffic has significantly increased energy consumption in mobile networks, leading to higher operational costs and environmental concerns. This paper presents a detailed energy modeling approach for critical mobile network components. By developing mathematical models for computing, processing, and memory resources, this study identifies a considerable energy proportionality gap in core computing, where servers maintain a baseline power consumption of 40-60% even during idle periods. Further, comparative analysis reveals that the RAN is the most demanding energy user, accounting for 70-85% of total network power. The results demonstrate that while load reduction offers minor gains, implementing advanced deep sleep states in base stations can reduce power consumption by up to 85%. Strategic energy management must target the major power consumption of the RAN and the high idle power of core resources to achieve meaningful sustainability benefits.