Energy crisis and calls for climate action – Is there an immediate solution for telecom operators?

By Mohammad Nur-A-Alam, Head of Sustainable Analytics Products, Nokia.

With urgent action need to address climate challenges, leaders and policymakers are preparing for the United Nations’ latest Climate Change Conference, COP27, set to be held in Egypt.

Telecom operators and enterprises are playing their part in addressing net zero actions by working within the ESG frameworks of Scope 1, 2 & 3 emission categories. However, it’s clear that working towards net zero is currently an expensive prospect, requiring a step-by-step approach based on significant technology innovations alongside policy support.

A mid-size communication service provider (CSP) consumes approximately 300 – 350 GWh of electricity a year, and with rising scarcity and increased cost of electricity per KWh, CSPs are struggling to keep their OPEX stable. In recent discussions with top CSP executives, one question keeps recurring – how can I keep my energy costs at the same level?

As they evolve, CPE/UE, RAN and core software features, SoC & architectures for Mobile, fixed and Data Center networks are adding energy efficiency at every step. Adopting an end-to-end energy solution, covering both AI/ML software-based sleep and hard switch-off, together with site auxiliary savings, can reduce energy consumption by up to 60%. In actual numbers, this means a cut in electricity consumption of 200 GWh. But how do we get there?


AI-Based Reduced Energy Consumption: 

The answer lies in an AI-based approach, along with the help of data science. Some key features of AI-based energy reduction products should be –

  1. AI-based soft sleep of RAN equipment – Typically, RAN sites are installed with 2G/3G/4G/5G radio & system modules. AI algorithms can assess the load on the RAN and command a soft switch-off. CSPs can usually save 8-15% on top of their traditional savings programs.
  2. AI-biased hard switch off for RAN equipment – Once the savings window is identified by the AI-based soft sleep, further cuts in energy consumption are possible with a hard switch off. Our study shows that 10% additional savings can be added on top of using soft switches. However, CSPs must be careful with legacy equipment in the network – usually, newer technology like 4G and 5G equipment is more robust and can achieve these extra savings safely.
  3. AI-biased AC control for site auxiliary energy savings – A typical AC consumes 2.2 kWh during load conditions, whereas standby mode uses only 100Wh. AI-based air conditioning can massively reduce the operating time and level of cooling systems throughout the day.
  4. Intelligent fresh air ventilator for natural cooling – AI can manage the exchange of hot and cold air inside and outside equipment sites, using high precision temperature control to save on the energy used in air conditioning. Since every site is different, the AI engine and automation calculates and adapts precisely to the specific site conditions.
  5. AI-based anomaly detection – Some faulty or aged equipment in the network typically consumes more power than usual and AI should be able to flag network elements for replacement, allowing extra savings and improving network performance.


Additionally, these insights provide a view of overall network level energy consumption as well as savings for each network element, giving business analysts and management a comprehensive view to plan their next steps.

For AI-based soft and hard switch-off, operators need a product that can maintain all major network performance KPI & QoE levels intact – for a critical network infrastructure, quality degradations are not an option.


AI-based truck roll reduction   

A CSP’s network consists of 10 – 50,000 or even more sites depending on the country’s population and geography. These sites are installed with operational equipment to run critical network infrastructures and need periodic and reactive maintenance to maintain optimal network performance. Each year will see around 100,000 site visits performed, with each visit needing truck rolls that contribute to significant costs and CO2 emissions. With AI-based truck roll reduction, operators can reduce the number of site visits by approximately 15 – 20%.


Nokia has leading products for both AI-based energy and truck roll reductions, helping CSPs and enterprises worldwide to fight the energy crisis and tackle climate change.

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