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Cutting network energy Opex without compromising user experience

Analytics
Assaf Aloni, VP marketing of CellMining, believes that using data analytics to control smart power shutdown in cellular networks can offer significant energy savings without risking the quality of customer experience.

All telecom network operators worry about Opex, and energy costs can be a significant part of this. It has been quoted in the past that energy costs made up approximately 50 percent of the total operating cost of a cell site in India, and 25 percent of an operator’s total Opex.

Many cell sites are off-grid, meaning that energy has to be provided either by diesel generators or – more recently – by renewable energy sources. Many more have fragile electricity supplies that are only available for part of each day, which therefore require diesel generators as backup.

Network energy demands will continue to grow with the exponential increase in user traffic, so there is a powerful incentive for operators to find ways of reducing the financial impact. Powering down base stations at times of lower demand may seem a simple option to minimize energy Opex, but if this can only be achieved at the expense of degrading user experience (and the associated risk of customer churn) then it can prove to be a false economy.

A further challenge is that each time a new generation of radio access technologies has been developed, there has typically been a considerable reduction in efficiency of the amplifier stage because of the evolving characteristics of the transmitted signal, in particular the Peak to Average Power Ratio (PAPR). So a new technology generation increases demand, therefore increasing energy consumption, while at the same time reducing efficiency, thereby creating a two-fold detrimental effect on energy costs.

Spiraling energy consumption by the telecoms industry is a huge concern for climate change as well as for network operators’ finances, especially where diesel is being used. Even back in 2011 a study in California estimated that the mobile networks’ consumption of electricity globally was more than 60 billion kWh – costing more than $10 billion per year – and corresponding to tens of billions of metric tons of CO2. More recent academic work sees these consumption figures as doubling every five years, and estimates environmental impact to already be on a par with that of the aviation industry.

A number of measures have already been put in place by the industry in an attempt to minimize energy consumption. These include more efficient power amplifier designs incorporating envelope tracking, MIMO and radio resource management techniques, the use of remote radio heads (RRH), and the trend towards smaller cells. Techniques for spectrum balancing – reducing the number of frequency bands in operation at off-peak times – and of selective power-down of base station have also been introduced, but without feedback regarding the effect on users this risks compromising their quality of experience.

Starting with a simple timetable for shutting down and powering up RF power amplifiers during pre-scheduled nightly slots, it is possible to establish cell analytics and develop more sophisticated algorithms to track subscriber usage patterns day and night. Drilling down through the data to the subscriber and device level yields an accurate set of user profiles that can be used as the basis for informed energy saving decisions, thus delivering subscriber-aware energy savings. Multiple parameters can be included in the calculations, including network technology, frequency bands, carriers, and peak/off-peak time slots.

Major highways and traffic routes can be particularly unpredictable: in the case of a train breakdown, serious road accident or unexpected traffic jam, certain sectors may need to be rapidly powered back up. Large sporting or entertainment events will also be exceptions to normal operating profiles.

Over time it may become obvious that certain key cells will always have a negative impact on user experience if powered down, and these can be excluded from shutdown schedules.

Energy savings can be categorized as either risk-free saving and CX-risking savings. With a multilayer radio shutdown scheme, off-peak savings can be risk-free while also being considerably higher than those achieved with a single-layer timetabled approach. At peak times the difference is even more marked: the smart approach delivers much bigger savings at a greatly-reduced risk to customer experience.

By Assaf Aloni, VP marketing of CellMining

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