U.K. network monitoring company Arieso made a big splash in the U.S. in January, when it published figures showing that the iPhone 4S consumed double the amount of data of its Apple smartphone predecessors, a trend Arieso attributed to the device’s new voice interface Siri. Several months and — Arieso claims – several misconstrued quotes later, Arieso is again hoping to make leave a mark on the U.S. wireless market, though perhaps not one so controversial.
In a recent interview, CTO Mike Flanagan said Arieso is working with a major U.S. carrier to plan for the advent of small cells. He wouldn’t name the operator, saying only it was a Tier I player, but that operator was using its network analysis and optimization tools to identify areas of high-congestion in the network – both in specific locations and from specific customers, Flanagan said. Those analytics can then be used to plan the operator’s future network expansion with precision. Rather than add an expensive layer of bandwidth throughout the network, Flanagan said, carriers could target only the areas where they need the extra bandwidth, on a cell-by-cell and even a customer-by-customer basis.
“If you are living on this planet, spectrum arrives slowly,” Flanagan said. Carriers can no longer count on spectrum being readily available for new networks, as evidenced by Verizon Wireless and AT&Ts’ to sort out what airwaves remain. “The answer is not to necessarily build new networks but improve the signal-to-noise ratio of the existing ones,” Flanagan said.
By signal-to-noise ratio, Flanagan is referring to basic quandary of cellular network design: the further away a device is from the tower, the more noise is introduced into the transmission, impairing signal strength and reducing bandwidth available over the connection. Building networks that can minimize that problem is the goal of an emerging tech sector of the wireless industry called self-optimizing networks, or SON. In my recent Long View analysis in GigaOM Pro (subscription required), I explore how technologies like Arieso’s and Intucell’s aim to use SON technologies to create more consistent, more resilient and higher-capacity networks by making them multi-layered and agile.
In Arieso’s case SON means planning upgrades to the network with surgical precision. In Europe, Vodafone is already using Arieso’s platforms to pinpoint problem spots in its networks, Flanagan said.
“For instance, if I have a customer who lives right at the edge of a cell consuming enormous amounts of data, he’s messing up the network for everyone else using that cell,” Flanagan said. Rather than try to boot that customer off the network, the carrier could offer that customer a femtocell or deploy a public small cell in his vicinity, both of which would suddenly free up network resources for everyone else. “For less than a $ 1000 investment, I clear up a capacity problem, and assuming it’s a good customer paying a $ 100 monthly bill, I get a return on that investment after a year.”
Operators aren’t going to go around placing individual cells for every customer, but the level of precision Arieso’s planning tools allow can be scaled network-wide, allowing operators to deploy heterogeneous networks, or hetnets, using small cells to build high-density clusters of capacity under the macro network umbrella. Right now, Arieso’s technology isn’t true SON because there’s no “self”-actualizing component — carriers still have to install those new cells manually. But Flanagan said that Arieso’s platform could eventually become the basis for dynamically self-optimizing systems like those being deployed by Intucell today. In such a scenario, operators don’t react to congestion problems by installing new base station. Instead the network itself reconfigures itself on the fly to meet traffic demands, following congestion as it moves through the network.
Cells image courtesy of Flickr user Patrick Hoesly
Related research and analysis from GigaOM Pro:
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- Self-optimized networks: solving the capacity crunch
- LTE-Advanced: what it is and isn’t
- Updated: Forecast: global mobile subscribers, 2010–2015
