AI, machine learning could put cell sites to sleep (and slash energy costs)

Wireless operators spend millions of dollars every year paying for the electricity to power their cell sites and small cells. But there are new energy-saving features that are being developed that could make a dramatic difference in energy consumption. And these new features incorporate tools like artificial intelligence (AI) and machine learning.

In a new Ericsson white paper called “Breaking the Energy Curve,” the company said that machine learning can be used to make certain network features more autonomous. Two of those features, MIMO Sleep Mode and Cell Sleep Mode, are using machine learning to study data traffic patterns and save operators money.

For example, in a cell site with a 4×4 multiple-input multiple-output (MIMO) antenna, a machine learning algorithm for “Sleep Mode” can analyze traffic and then predict when the site should use all four radios or just one radio. Ericsson said that in trials, this technology was found to save operators about 14% in energy consumption per cell site.

Similarly, machine learning can also be used to detect low-traffic conditions and using Cell Sleep Mode can turn the cell site off. The software then monitors traffic conditions and will turn the sleeping cell back on when those conditions change.

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