Making the 4G transition

4G is rapidly becoming a mainstream technology, accessible to mobile subscribers throughout the UK and Europe. 4G has brought with it a number of new use cases such as video streaming and gaming, plus the highly anticipated voice-over LTE (VoLTE), which will feature voice and video calling services delivered over mobile networks. However, due to this change, it’s no longer enough for operators to just maintain their networks for voice, messaging and data; they now have to deal with a whole range of new complexities. As a result of this paradigm shift in telecommunications, it is vital that operators develop a much better understanding of the subscriber and how they engage with the network and operator services. They need to implement end-to-end service assurance and optimisation tools that cover the entire network from the RAN through to the core.

The RAN poses a big challenge to the operators, yet it’s very important that they can get as close to the subscriber as possible, especially since network use cases have changed. Optimising the RAN for voice and messaging is no longer enough; operators need real-time intelligence about what is happening at the network edge, what services and applications subscribers are using, and on what kind of device. Our research has shown that even a relatively small concentration of users can represent a high proportion of data traffic, and can occupy available cell capacity. In this type of situation, an operator will be delivering a satisfying experience to some subscribers, but a sub-standard experience to others. With the move to LTE creating more unpredictable data requirements, service assurance and monitoring tools that deliver these essential insights have become more important to carrier operations. Insights into subscriber behaviour and network performance can only come about through an end-to-end view of the network, which takes into account the differences between subscribers.

It is now possible to apply a rich layer of geo-analytics and visualisation tools for the RAN, enabling operators to dynamically pinpoint issues at the subscriber and network level in real-time. These tools can also support RF planning and network optimisation for 4G networks. Up to 70% of subscriber issues occur inside the RAN and at least 10% of those problems are not resolvable with existing basic monitoring workflows. Evidently, this is a major concern for operators at a time where a minority of users can impact the Quality of Experience for the majority, potentially leading to widespread churn and loss of revenues. Until now, the use of RAN probes and NEM-based cell trace functionality to glean information from mobile devices used by subscribers has been the standard industry approach for spotting network problems and getting them fixed. The accepted method is to interrogate the data that comes in, assess the performance of individual cells and then react accordingly. In the case of heavy data users, the most commonly deployed tactic is to offload subscribers to small cells and direct traffic away from the congested macro cell.

This approach, however, poses a very significant problem; it’s reactive, not proactive. The very notion of identifying a problem in the network based on handset statistics and cell performance means that a valuable subscriber has already received a poor customer experience. In turn, this means that their level of satisfaction has taken a knock; the experience has been less than excellent. And if operators find themselves playing ‘catch up’ with the user experience at this stage, once more data starts flowing across their networks as they continue to expand 4G coverage, it’s likely they will only fall further in the eyes of their users.

Delivering on the 4G promise

The success of a next generation mobile network lies in an operator living up to the promises made to its subscribers. In order to handle network performance more efficiently, operators need to gain actionable insights into the user experience that they can leverage to deliver consistent and reliable mobile connectivity. As a result, to keep pace with subscriber expectations, operators need to adopt new strategies to deal with network issues before they arise and improve the overall user experience. There’s a way to make extremely smart use of network data to go beyond the spot/fix approach, but this requires operators to collect information from the RAN that not only addresses troubleshooting issues but also empowers better targeting in setting up location-based services, future-proofing through more advanced network planning, and better informing engineering decisions in a way that’s simply not possible with current monitoring workflows – the ones that can’t solve the 10% of problems.

The only way to achieve this is to make user-centric data observations, drilling down into targeted demographics and developing the network model based on deep insights into the needs, behaviours and usage patterns of subscribers. It would be difficult to produce these insights without an end-to-end view of the network, which takes into account the differences between users and their individual requirements. The process of analysing cell sites with data probes can be automated to identify precisely where it would be suitable to hand over to small cells, and operators can also adopt solutions that collect radio interface signalling information to calculate the geo-located coordinates of subscribers generated by their mobile devices. RAN data can even be used to reduce the need for drive tests, by collecting and analysing dropped calls and data traffic from network ‘heat maps’.

Blueprint for the future

U.S. operators are ahead of the curve in building out their LTE propositions, which already cover more than 90% of the population. This compares with 47% coverage in Europe and 10% in Asia. However, by rolling out 4G, these forward thinking 4G operators have provided a blueprint to success for carriers in other regions. By using geoanalytics and visualisation tools for the RAN, operators can dynamically pinpoint issues at the subscriber level in real-time, track those issues across the network and identify new up-sell opportunities based on individual subscriber needs. By having a complete end-to-end view of the network, subscriber data pulled from the RAN can now be used to support a wide range of departments from engineering to customer care.

It’s clear that deep network intelligence will form some of the most important operational and business decisions in the immediate future, yet too often the most useful information remains hidden deep within the network. By unlocking the value of subscriber data contained within the RAN, operators will be in a better position to provide a strong Quality of Experience and retain subscribers in the long run. Ultimately, happy networks will lead to happy subscribers.