CSPs Committed To Sustainability Aim To Reduce Power Consumption
One of Japan’s largest communications service providers (CSP), serving over 60 million subscribers nationwide, is committed to fostering a sustainable, decarbonized future.
This commitment is outlined in their Green Plan, where the company sets a target to reduce carbon emissions by 50% in 2030 compared to 2019. The organization recognizes the pivotal role of curbing power consumption in its base stations to attain this ambitious goal.
Challenge | Reducing Power Usage While Implementing AI-Powered RAN
The company’s radio access network (RAN) accounts for approximately 60% of its total energy consumption, making reducing power usage in these stations a vital initial step. However, effectively managing and perpetually optimizing network energy consumption necessitates collecting and analyzing substantial volumes of data from diverse sources—a task that is impractical to perform manually.
In response to this challenge, the business sought an AI-powered network energy management system capable of assessing real-time demand and traffic patterns, seamlessly adjusting the power consumption of RAN resources to match this demand automatically.
To ensure this system could achieve these objectives without compromising the premium user experience expected by its subscribers, the organization collaborated with Nokia to conduct trials on Japan’s first-ever AI-controlled RAN.
Solution | Nokia’s AVA for Energy Efficiency
Implementing a strategy of deactivating idle network components during periods of low traffic holds immense potential for CSPs to achieve substantial energy conservation. In the context of this pilot project, the organization harnessed the AI-powered capabilities of Nokia AVA for Energy Efficiency to execute precise forecasts. These predictions were pivotal in synchronizing power consumption, network performance, and customer experience requisites.
Nokia AVA for Energy Efficiency employs AI to review and predict fluctuations in traffic levels within the regions and cells of a RAN. It strategically identifies moments when radio resources can be powered down to reduce energy usage while coordinating actions across adjacent cells to optimize energy savings across a coverage area. For example, in situations with overlapping coverage, a cell may be deactivated entirely during periods of minimal traffic as long as the surrounding cells adequately serve the area.
Nokia AVA for Energy Efficiency monitors network performance to safeguard the organization’s customers from adverse effects when radio resources are temporarily placed in a standby state. It promptly reactivates cells if unexpected network performance deterioration is detected and rectifies cell conditions in the event of faults. Moreover, it gives the organization the flexibility to intervene manually whenever necessary.
This approach marks a departure from the conventional method of network energy management, which relies on manual, static schedules for toggling radio resources on and off.
Nokia AVA for Energy Efficiency advances the paradigm by instigating predictive, closed-loop actions that enable swift, automated responses to evolving conditions. This strategy optimizes energy savings and preserves network quality simultaneously.
Result | Advanced Energy Efficiency
The organization achieved a remarkable reduction in power consumption by incorporating a liquid coolant known for its superior cooling efficiency compared to traditional air-based cooling mechanisms. Specifically, this innovation targets a decrease of over 70 percent in the power consumption of the air conditioning systems responsible for cooling the rooms housing its base station facilities.
This forward-thinking approach signifies the organization’s dedication to advancing energy-efficient technologies in the telecommunications sector and aligns with its broader commitment to environmental sustainability.
Benefits | Reducing Power Consumption Without Reducing Performance
Nokia AVA for Energy Efficiency employs a calculation-driven approach to determine when radio resources can be placed in sleep mode, considering the daily performance requirements for every cell. This innovative system can establish extensive energy-saving intervals while consistently meeting the organization’s desired customer experience benchmarks. Throughout the pilot program, specific cells were powered down for approximately eight to nine hours each day.
The outcomes were compelling. On average, the organization achieved a remarkable reduction in power consumption of up to 50 percent in low-traffic scenarios, with individual cells realizing savings of up to 20 percent.
Furthermore:
- Nokia AVA for Energy Efficiency delivered these energy savings without adversely impacting network performance. Despite the substantial daily sleep-state intervals, there were no issues, such as traffic congestion in neighboring cells or alarms. Consequently, the user experience remained largely unaffected.
- Remarkably, the project was set up swiftly, requiring only four weeks, including establishing the data pipeline essential for the AI algorithm. This efficient setup contributed to rapid energy-saving results.
Although this project centered on Nokia radio equipment, it’s important to note that Nokia AVA for Energy Efficiency is fully multi-vendor compatible. This means it can be deployed across any of the organization’s base stations throughout Japan.
Encouraged by the positive outcomes of this trial, the organization intends to implement AI-driven energy management across its entire commercial operations network. The collaboration between the organization and Nokia will persist, with a shared commitment to researching and developing systems that can further diminish the carbon footprint of base stations.
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