A Machine Learning Mechanism for Improved Energy Consumption in 5G Small Cells

By introducing 5G networks in our lives, we are faced with the challenge to lower energy consumption, which is expected to increase significantly. As a result, the communications sector must devise solutions to improve the energy efficiency of 5G networks while maintaining spectrum performance. We propose a Machine Learning Mechanism that provides new sleep mode functionalities, that reduce energy consumption during idle hours, on small cells. We will describe our model and examine its performance using data collected from a simulated environment. Furthermore, we present the results of our findings and conclude that such models are necessary for the introduction of 5G networks. Lastly, possible future steps, are discussed.