Written by Yanitsa Boyadzhieva
- A new report from the NGMN Alliance focuses on mobile network energy efficiency options
- It highlights actions mobile operators can take in the short, medium and long term
- The alliance calls for further research on the energy-saving potential of key technologies, including machine learning (ML) and cloudification
The use of machine learning (ML) tools, the redesign of cell sites and investment in emerging technologies are among the key approaches that mobile operators can take to improve the energy efficiency of their radio access networks, according to a new report from the Next Generation Mobile Networks Alliance (NGMN).
In its latest report, “Green Future Networks: Network Energy Efficiency Phase 2”, the NGMN offers a roadmap for reducing the energy consumption of mobile networks and highlights gains that can be achieved in the short, medium and long term.
Short-term energy efficiency gains can be made by putting an immediate focus on process optimisation, according to the industry body, adding that it is possible to reduce energy consumption in a radio access network (RAN) by up to 10% by “optimally configuring networks to use existing power-saving features”. In this scenario, ML tools can be used to calculate the energy-saving potential of various power-saving schemes and identify which processes to prioritise, the report suggests.
