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AVA – Energy efficiency

For cost-efficient and sustainable networks

AI can reduce CO2 emissions and network energy costs, with no negative impact on performance or end customer experience. As energy consumption already accounts for about half of all telco network operations cost, 78% of telcos are counting on AI energy solutions to cut energy use.

With the pressure coming from the Paris Accord, and from the cost side as well, you must choose the best strategies to shrink the carbon footprint of your networks and achieve your sustainability commitments. AI-based energy management automation can be the fast track to solving both issues.

How Artificial Intelligence reduces the carbon footprint of telco networks

Did you know 78% of telcos are counting on AI energy solutions to cut energy use? From the originally produced energy in power plants only 90% “arrive” at the network, so there is already a loss of 10% during energy transmission. From this remaining energy about 80% is consumed by the radio access, the rest by transport, core and OSS. 30% of that network energy (35% of the original energy) is consumed by auxiliary passive components such as air conditioning and power systems, so that only 70% (65% of the original energy) is consumed by the network elements itself.

Site solutions for energy are extremely important. Power hungry fans and power supplies consume another 20%, only the rest arrives at the chipsets as such and can be used for transmitting traffic. From that remaining energy only 30% is really used in a productive revenue generating way since on average most resources are running idle. Therefore, AI based solutions performing dynamic shutdowns of unused resources are key. In effect 85% of the original energy “disappears” and is not used productively.

Benefits of AI energy management for mobile networks

Up to 30% energy savings and less CO2 emission for telco radio networks

Energy cost savings are achieved within weeks due to quick setup times

2-5x more power savings than non-AI systems that perform temporary shutdowns based on fixed schedules

Up to 70% less energy consumption
for cooling

Minimizes all kinds of energy waste
across active radio and auxiliary equipment

No impact on network performance while dynamically shutting down network resources

No large-scale deployments
and hardware changes needed


How China Mobile is using AI for energy efficiency

Nokia AVA - AI Energy Efficiency capabilities for telco networks

How to make AI energy management for networks happen

Because of its software nature, AI-based energy efficiency solutions can be deployed in just a few weeks without major upfront investment — especially thanks to outcome-based Software-as-a-Service (SaaS) business models, which enable you to pay only for the energy savings outcomes you actually achieve. Implementing the AI system over a public cloud can make it even faster by easing the processing and analysis of the large volume and velocity of network data.

Real-world experience shows that AI-driven automation can be implemented in a matter of weeks, making it the most immediate opportunity for large cost savings. We have seen power savings in real networks from seven percent to 30 percent. Since Nokia AVA for Energy Efficiency is multi-vendor these savings apply to not just the equipment of a single RAN vendor but the whole network.

As a total-site software-based telco energy solution, an AI system can be set up quickly to minimize all kinds of energy waste.

Your network is wasting energy. AI can change that in a flash

For any CSPs out there who have been waiting for the right solution to come along and help them meet their sustainability goals with energy savings: the wait is over.

Find out how

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