Mobile operators around the globe have largely given up on ownership of content, and now find themselves in a position where they’re competing on price—which involves extremely thin margins. It’s not a sustainable scenario, particularly in very competitive markets, so they are seeking ways to differentiate the user experience of their subscribers.
But, that’s often easier said than done.
Several factors are at play here:
- Network utilization is being driven to breaking point, thanks to the growth of over-the-top (OTT) services.
- Rapidly shifting changes to user traffic behaviors (Pokemon, anyone?) make managing quality of experience (QoE) difficult.
- To successfully monetize LTE investments, operators must precisely align the performance of core and transport elements—a tricky and delicate balance to strike.
Taken together, this creates a new type of market dynamic: The Quality Wars. And, the war has now come to India. There are more than a billion potential subscribers in the region, and battle lines are being drawn between Vodafone India, Bharti Airtel, Idea Cellular, and Reliance Jio, each of whom wants to grab as much of that market share as possible.
The challenge of LTE QoE
To emerge victorious, these service providers obviously need more capacity. But, this additional capacity cannot be obtained in the traditional way of simply throwing money at additional infrastructure, and spectrum is a finite resource. The “work smarter, not harder” adage is very apt here.
Information is key to winning this war—specifically, network-wide information about traffic performance and its impact on the user experience. Why is this so crucial?
Optimizing QoE for LTE network users is a highly sensitive process where microscopic effects, like tiny amounts of lost or delayed packets, can have large scale consequences. Predicting, diagnosing, and troubleshooting such issues is extremely difficult, if not impossible, without network-wide insight into traffic behavior and user experience across the entire network, from core to edge.
Winning the war with virtualised instrumentation
To address the issue of QoE as it relates to LTE services, operators in India are investing in advanced, software-based solutions that support end-to-end visibility into network quality of service (QoS) and user QoE.
This is Accedian’s specialism: we’ve spent a decade developing centrally-managed instrumentation that can be deployed network-wide. This is now available in virtualised/software-based format, so operators can deploy an instrumentation layer quickly and affordably.
Such an instrumentation layer provides a granular, real-time, complete picture of how well services and applications are performing. Service providers can take this insight and feed it into big data analytics platform to reach meaningful conclusions about what’s going on and where there are issues. Control systems can then make smart decisions about how to allocate network resources to optimize QoE in the most lucrative way possible.
There are some interesting cases where, by employing this strategy, operators uncovered correlations previously invisible (and therefore ignored) responsible for network glitches significantly affecting end user QoE.
In one case, a major Indian carrier was launching a new LTE network, aiming to win millions of subscribers in less than a year. But, in an entire major metro area, the network was experiencing systemic, recurring, large-scale VoLTE call failures, impacting hundreds of thousands of users. The network seemed to be behaving normally, and in fact utilization was less than 20 percent: there appeared to be no problems when measured by normal metrics. But using the microscope of virtualised instrumentation, examined by a big data system, the operator discovered unusual correlations: antenna angle, software versions, and VoLTE call drops were interrelated, causing severe degradation. Once they knew where to look, the operator resolved the issue within 10 minutes.
Virtualised instrumentation isn’t just useful for solving LTE performance issues. It can also be a powerful tool to get more out of existing network infrastructure. For example, a major Asian carrier spent a month using machine learning to dig into overall network performance. After that period, Accedian was able to suggest three areas of network improvement that would deliver 97 percent more network capacity and speed within 30 days, without any new capital investment or spectrum.
Conclusion
When virtualised networks, performance instrumentation, and big data analytics come together optimally, the result is an ultra-reliable network capable of consistently delivering high-quality service. That’s the winning formula to capitalize on short-term, lucrative revenue opportunities and also build loyalty and customer dependency over the long term.
By Dave Dial, Vice President International Sales at Accedian Networks.
