Arieso has revealed statistics showing that mobile operators could potentially save more than $560 million in operational expenditure annually by “powering down” redundant base stations.
By analyzing actual subscriber network traffic data that indicates network capacity demand, Arieso believes that around 390,000 base stations can be powered down during quiet night time periods, saving more than 3.5 billion KWh of electrical power.
Thanks to out-dated network measurement techniques, many operators have not had access to precise data that tells them exactly where and when traffic demand exists, and where and when base stations are most needed. Crucially, this information could help operators understand which base stations can be powered down and for how long, without affecting the consumer experience.
As consumer appetite for mobile data continues to rise, operators have sought to add more network capacity by deploying new base stations in densely populated areas, or busy urban zones. New base stations may help solve capacity issues during peak hours, but during the dead of night, many of these base stations become redundant – yet still consume the same amount of power.
Using standard industry figures, Arieso has also calculated that this unnecessary power consumption needlessly contributes large volumes of harmful CO2 to the earth’s atmosphere.
Reducing the 3.5 billion KWh consumption shown in this study equates to a reduction of 1.9 million metric tons of CO2e (1.9 Mt CO2e). Eliminating these emissions would be equivalent to taking approximately 478,000 cars off the road each year, globally.
Typical mobile networks are designed to serve peak traffic (voice calls and data sessions) demand. However, in off-peak periods, traffic demand falls significantly, requiring just a fraction of the total available resources. In effect, network capacity provided for peak traffic becomes redundant during quite periods.
Using actual customer usage data, Arieso monitors the real-world impact of data and voice calls in precise locations, and determines their effects on overall network performance.