Exclusive Interviews

With geolocation, mobile operators can find, determine and provide the exact location of a mobile phone (user) on their network. Geolocation is used in a variety of applications like troubleshooting and analytics, and opens up a whole range of possibilities for data monetization. In an interview with Telecom Review, Vicent Soler, EVP CTO Spain - Advanced RAN Studies, Astellia, talked about the importance of geolocation and its benefits.

Can you provide some concrete use cases of how network engineers can benefit from geolocation?
With geolocation, operators can have massive coverage maps and thereby it becomes much easier to identify any area with coverage holes, congestion or dropped calls. This allows network engineers to become much more efficient because they can focus network deployment and troubleshooting activities on these specific areas. Subsequently, this will have a concrete and positive impact on the subscriber experience.

Another relevant benefit of geolocation information for network engineers is that it helps accelerate the introduction of new technologies. It can help them, for instance, to identify where there is a high concentration of VoLTE capable mobile phones in the network in order to reinforce 4G coverage in these areas to ensure an optimal VoLTE experience.

At the moment operators are looking for solutions to offload the traffic from the macro cells. In this case, having information about where subscribers are located is very useful to define the right position to deploy new small cells.

Can geolocation information reduce the need for drive tests?
Yes, definitely. This is clearly one of the main benefits that geolocation brings to operators. By actively using geolocation information operators can save a lot of money. From Astellia's experience, we have seen that operators can reduce up to 90 percent of their investments in drive tests. A drive test is very costly because it is a manual procedure - you have to send a team into the field to launch measurements at each location. Additionally, drive tests can only generate a dozen of tests and therefore do not reflect the whole customer experience. They do not provide historical data and data is not available instantaneously. Furthermore, drive tests are often inefficient at reproducing an issue reported by a subscriber since the tests are performed outdoors. However, 70 percent of voice calls and 80 percent of data sessions occur indoors. So, in contrast to geolocation, drive tests do not provide a complete view of the customer experience.

How can geolocation information enrich customer experience management (CEM)?
Geolocation information increases customer care efficiency. By positioning failed calls on a map and analyzing subscriber mobility during a call, customer care agents will better understand a complaining subscriber and can bring a solution more quickly, not only to the complaining customer but also to all the subscribers in that area.

Each element that provides additional information on the customer, provides a better knowledge of that customer and hence insights to improve their experience. Valuable subscriber mobility information can be used to geolocate high revenue generating areas (roamers, VoLTE subscribers, fleets, etc.), determine the customer experience of these hot spots and avoid potential loss of revenues due to a bad functioning network in these areas.

How does geolocation data contribute to new revenue generation?
With the current internet of things (IoT) revolution, asset tracking is becoming a revenue generating and value-added service offered by operators to their enterprise customers. So being able to provide massive geolocation of low-cost IoT devices without costly GPS functionality is a clear competitive differentiator.

Marketing can exploit geolocation data to create additional revenues by, for instance, engaging with a customer accessing a predefined area. Some examples of use cases are location-based advertising, analysis of population flows for road traffic information, helping shopping malls understand where their customers are coming from and the time they are spending at their premises, etc.

What makes Astellia's geolocation solution unique?
First of all, Astellia's solution offers the best-in-class geolocation accuracy. Its algorithm is based on trilateration, minimization of drive tests (MDT) and includes machine learning evolution. It goes much further than providing a visibility at cell level; it gives a precision as near as 100m and with an evolution to less than 50 m with our latest innovations. It allows operators to distinguish indoor and outdoor communications and characterize static vs subscribers in motion, all while preserving individual customer privacy.

Through its 3D geolocation feature, the solution can represent on a map distinct quality of service (QoS) and quality of experience (QoE) for each floor of a building. Astellia's massive geolocation solution provides geolocated QoE of popular apps such as video (YouTube) and social media (Facebook). This allows engineers to adapt capacity for high-trafficking value-generating areas.

Astellia's awarded solution gives a real-time, end-to-end vision (RAN to Core) of the network, 24x7, for 100 percent of the calls. It is the first solution on the market to geolocate IoT devices on LoRA networks. This future-proof solution is completely virtualized and big data ready, and is already adopted by several major operator groups such as Telefonica to better optimize their network and improve the customer experience.

In an interview with Telecom Review, Ali Wansa, managing director, Astellia Middle East, talked about the geolocation and RAN optimization's importance which brings benefits to the operators. 

How are you helping operators gain deep understanding of customer behavior?
The telecoms market is rapidly evolving from a voice-centric to a data-centric market. This brings the need for mobile operators to change the way they interact with their customers and develop a deep understanding of their subscribers with a personalized approach. This requires operators to segment their customer base since usage and revenues are no longer enough of differentiators to cluster customers.

We have been working, for instance, with Zain to help them better understand subscriber's center of interest and behavior by analyzing customers' application usage (number of sessions, session duration, bandwidth usage, geolocation, etc.). By using Astellia's Nova Customer Analytics, we could clearly distinguish different types of behavior which led us to revise together the CRM-based segments and implement new customer segmentation. This has led to the creation of the new 'Big Gigs Family' offering.

We are now monitoring each new segment per offer to understand their behavior and see if there is any change in data consumption. We pay particular attention to the impact on the network of each new offer by monitoring for instance the busy hour throughput per offer. We anticipate that the immense success of the 'Hero' offer (unlimited data usage, free 4G device, unlimited downloads @night) will put pressure on network resources.

Zain uses this new segmentation to recommend the right offer in order to optimize network resources and enhance profitability of data services. It should be noted, however, that dynamic segmentation is a perpetual process, and continuous fine-tuning is needed in order to optimize revenues and control the impact on the network.

On what are you specifically focusing to improve customer experience?
A multitude of elements have an impact on the customer experience: device and OS type, latency, congestion, applications used, network topology, location, time, etc.

In order to decide how and where to optimize the network and to ensure a good customer experience, mobile operators need a holistic, end-to-end view of the subscriber, network, device and application interactions.

Astellia's solution correlates control plane, user plane and call trace information. It thereby provides this end-to-end view, from radio all the way up to the core with precise geolocation information.

This allows us to identify low-performing network elements, measure device impact on the network, benchmark handsets, analyze application usage and understand customer mobility.

So, Astellia not only brings this 360° vision of the subscriber experience, but also identifies the root cause of the problems a subscriber might face.

How does RAN optimization play a key role in securing network efficiency and drive customer experience?
Eighty percent of quality and hence customer experience-impacting issues occur in the RAN. To provide a seamless user experience across radio access technologies and layers, it is extremely important for mobile operators to focus optimization activities on this part of the network.

Without performing any drive tests, Astellia's solution pinpoints coverage holes and traffic hotspots and detects bad RF conditions from a subscriber perspective.

We perform radio sanity checks, meaning that we provide automated analysis to detect incorrect radio settings in neighbor list optimization; BA list, PSC and PCI clashes; crossed sectors; cell overshooting, etc.

Astellia also guarantees configuration parameter consistency by identifying out-of-range values, missing elements and conflicting settings.

Networks are evolving into very complex multi-technology and heterogeneous environments (2G, 3G, 4G, WiFi, etc.). So automation of repetitive RAN optimization tasks is needed. It saves time and money, and allows radio engineers to focus their optimization activities on more complex issues, on high value customers and high-value locations like tourist attractions, shopping malls, business centers, roads, airports and high speed train lines. It helps operators move from network-centric to customer-centric optimization.

For instance, we helped Orange Spain to optimize its network for business travelers on board high-speed trains. These are very complex environments due to the high speed at which customers are moving, but Astellia managed to separate out those people who are actually on the train and focus optimization activities on these users. This allowed Orange to become the best service provider on high-speed trains in Spain and created a real competitive differentiator for them.

What kind of benefits does RAN optimization solutions bring to the operators?
Mobile operators can no longer massively add network capacity. They need to optimize the use of their existing equipment and radio resources first before investing in new capacity. For instance, RF coverage can be optimized by reducing interference or overshooting. They can reduce capex by reducing congestion through optimization of the antenna tilt or by adding a new carrier or by redefining engineering rules to move traffic between different carriers.

At the end, optimization not only means capex and opex reduction, but can mean an increase in revenues as well. By focusing optimization activities on high-value subscribers and on the most revenue-generating areas, there will be an increase in voice, SMS and data traffic and global revenues will be boosted.

Since MNOs are having a large interest for geolocation, which teams benefit from geolocation and in what way?
There are different use cases with geolocation. Geolocation represents, for instance, a very cost-efficient alternative to drive tests for measuring RF network quality; it can reduce field drive testing by 90 percent.

By the massive use of call traces we are collecting daily - hundreds of thousands of measurement reports on each cell, which includes geolocation information - we are hereby turning every subscriber into a drive-tester.

In contrast, drive tests can only generate a dozen measurement reports and therefore do not reflect the real customer experience. They do not provide historical data and data is not available instantaneously.

Additionally, drive tests are often inefficient at reproducing an issue reported by a subscriber, since 70 percent of voice calls and 80 percent of data sessions occur indoors. They only provide QoS snapshots at a certain moment in time.

Finally, drive tests do not provide any information on handset performance nor on application usage, which is critical when evaluating the customer experience.

With our Nova solution, mobile operators can benefit from up-to-date maps of their network coverage and performance. In order to obtain the same results with drive testing, it would require a long and costly drive test campaign, and thereafter measurements would have to be extrapolated to simulate overall coverage and network behavior, including indoor and outdoor maps.

Astellia also helps operators pinpoint black spots or coverage holes. If an optimization engineer is able to geolocate the areas with a high number of dropped calls, then he can focus his optimization efforts on that area.

Another relevant use case is small-cell planning. Right now, operators are looking for solutions to offload the traffic from the macro cells, and having information about where subscribers are located is very useful to define the right position to deploy new small cells.

Then, there are use cases not directly related to RAN optimization, but to support functions like marketing and customer care.

Marketing, for instance, can engage immediately with a customer entering a predefined area. Some examples of use cases are guaranteeing public safety by notifying people in real-time when they are entering a hazardous area; location-based advertising; analysis of population flows for road traffic information; analysis of catchment areas around commercial centers, etc.

Without geolocation information, it is hard to determine where an issue happened to a specific subscriber. If customer care agents can geolocate the area or cell where the problem occurred, they can diagnose whether the subscriber is the only one impacted or the problem is global to the cell. This is particularly useful to check if the subscriber is experiencing an already known issue, or to proactively prioritize network operations based on the number of impacted subscribers.

Digital Magazine

Dec 2016

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