Understanding LTE, inside and out
LTE changed the paradigm for mobile network operators and now, 4G is rapidly becoming standardized across the globe. Recent figures published by the Global Mobile Suppliers Association indicate that 288 operators have already launched LTE and it is now available in 104 countries around the world. The move has brought with it a number of new use cases such as video streaming and online gaming, plus the highly anticipated Voice over LTE (VoLTE) which is leading to high-quality voice and video calling services being delivered over mobile networks.
Yet, with this transformation taking place, it is no longer enough for operators to simply maintain their networks for traditional voice, messaging and data. As a result of this paradigm shift in telecommunications, it is now vital that operators develop a much better understanding of the network complexities and the ways subscribers engage with the network. However, this needn’t be an expensive or time consuming process, as operators already have access to this information – it’s hidden within the mobile network; all that’s required are the right keys to uncover it.
Operators that implement end-to-end service assurance and optimization tools covering the entire network from the RAN to the core can unlock this valuable data. RAN management and optimization is vital to delivering on the potential of LTE as it holds the keys to ensuring quality network performance for subscribers. But it comes with its own set of challenges, as historically it has been a very costly exercise for mobile operators. Not only that, but 70 percent of subscriber issues now occur inside the RAN, and at least 10 percent of those problems are not resolvable with existing monitoring workflows. So it comes as no surprise that having a better and more affordable approach to tackling the RAN is now a key technical and financial differentiator for operators, particularly as they’re also looking to recoup the considerable investments they’ve made on LTE network build-outs.
Resolving RAN issues
Because the nature of data fundamentally changed with LTE, network use cases have changed. It is no longer enough to optimize the RAN for voice and messaging alone; operators now require real-time intelligence into what’s happening at the network edge, what services and applications subscribers are using, and on which devices. A relatively small concentration of users typically represents a high proportion of data traffic and can occupy all available cell capacity. This means an operator will deliver a satisfying user experience to a minor subset of their overall subscriber base, but a sub-standard experience to the majority. It has become increasingly difficult to ensure a consistent quality of experience. Operators with access to service assurance and monitoring tools have the ability to fight back against customer dissatisfaction and churn, delivering essential insights for carrier operations that will not only help to alleviate network issues but also let them gain a greater understanding of the subscriber experience.
RAN congestion and intensive data users are a major concern for operators today. When a minority of users can impact the Quality of Experience for the majority, a less than stellar experience could lead to widespread churn and loss of revenues – at a time when operators are struggling to recoup network investments. Until now, the standard industry approach for spotting and fixing network problems has been through the use of RAN probes and NEM-based cell trace functionality to glean information from mobile devices used by subscribers. 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.
However, this approach is 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 their level of satisfaction has taken a knock. If operators find themselves playing ‘catch up’ with the user experience at this early stage, it’s likely they will only fall further in the eyes of their users once more data starts flowing across their networks as they continue to expand 4G coverage.
Alternatively, operators can access true insights into subscriber behavior and performance with an end-to-end view of the network that takes into account the differences between subscribers. So, to gather the necessary information, operators can apply RAN visualization and a rich depth of geoanalytics, giving them the ability to dynamically pinpoint issues at the subscriber and device level in real time.
Next generation solutions
The success of a next generation mobile network lies with an operator living up to promises made to subscribers. In order to handle network performance more efficiently, operators that pinpoint issues in real time can get a firmer grasp on user experience, and can deliver consistent and reliable mobile connectivity. To keep pace with subscriber expectations, and to improve the overall user experience, operators are adopting new strategies to deal with network issues before they arise. There is a way to make extremely smart use of network data to get beyond a simple spot/fix approach. However, this requires operators to collect information that addresses troubleshooting and empowers better targeting of location-based services, future-proofing through more advanced network planning. This ultimately better informs engineering decisions in a way that’s simply not possible with current monitoring workflows – the same ones that can’t solve the 10 percent of RAN problems.
The only way to achieve this is to make user and device centric data observations, drilling down into targeted demographics and developing the network model based on deep insights into the needs, behaviors and usage patterns of subscribers. An end-to-end network view takes into account the differences between users and their individual requirements. Operators automate cell-site analysis with data probes to identify precisely where it would be suitable to hand over to small cells and take on solutions that collect radio interface signaling information to calculate subscribers’ geolocation.
By adopting an end-to-end assurance solution that provides comprehensive radio access and core network analytics, operators can unlock a variety of new use cases for real-time subscriber intelligence and network engineering. The benefit is two-fold; on the one hand, this provides the ability to assure the customer experience across the entire mobile network, drilling down to the geolocated device and subscriber level. On the other hand, it provides the enhanced ability to deliver critical network intelligence that can be fed into numerous departments – from operations to customer care, and from the CMO’s office to the business development team. Real-time RAN data can play a vital role in reducing the need for costly drive tests, by collecting and analyzing dropped calls and data traffic from network heat maps. These tools can also support RF planning and 4G network optimization.
RF planning and network optimization
When it comes to using RAN data to support network planning, operators pinpoint exactly where network capacity is best employed. Once LTE networks are operational, the operator must then decide which areas of the network need to be prioritized for these capacity infills that can be addressed through small cells, in order to ensure a first-class subscriber experience.
It’s also key to consider how network upgrades interact with legacy infrastructure. The deployment and maintenance of an LTE network is a costly business, but big data can help operators optimize their networks in a cost-effective way. Through the use of geoanalytics, operators can generate a range of network performance data in order to make informed decisions.
This is all the more important as LTE becomes widespread and VoLTE deployments grow. Subscribers will undoubtedly experience ‘teething troubles’ when using these new networks. Network visualizing tools can help here, too. For example, customer care representatives can use real-time call and data session information to troubleshoot premium and other subscribers’ complaints – is it a network problem? A device problem? Customer care can then provide the engineering team with more actionable data to solve the issue, resulting in overall quicker time to resolution. This efficient workflow gives operators more freedom with their operational budget, which means they can limit the need to hire additional resources.
The new network intelligence
Armed with data and full network visualization, operators can dynamically pinpoint issues at the subscriber and device levels 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 customer care to marketing and all the way through to engineering.
Deep network intelligence will form some of the most important operational and business decisions in the immediate future, yet too often the most usual 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.
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