his guest post was written by Affandy Johan, Senior Product Marketing Manager, InfoVista

This guest post was written by Affandy Johan, Senior Product Marketing Manager, InfoVista

As of March 2015, LTE network coverage is now available for 98% of Americans, up from just over half of the U.S. population in 2011. Worldwide, 124 countries now have LTE coverage, with another 18 scheduled to roll out LTE this year. That represents a huge investment from governments and leading operators, which have each poured billions into bringing the speed and bandwidth of LTE to subscribers.

 Most mobile operators would agree that there are gaps in their processes for maintaining a high quality of experience (QoE) throughout LTE networks, though. While their goal is to quickly identify and address LTE network performance issues before they impact subscribers, many lack the necessary insight into subscriber and network data to accomplish this. As a result, LTE network optimization can be very challenging, often leading to subscriber churn when QoE falls short.

But, what if mobile operators could proactively combat this by thinking about performance from the subscriber perspective? What if they could troubleshoot their LTE networks based on data about subscriber QoE, rather than on just network KPIs?

While this may seem far from today’s service assurance processes, it’s actually not that much of a leap from current best practices. And, InfoVista is already helping mobile operators embrace this revolutionary new approach to mobile service assurance with a new solution to help mobile operators prioritize subscriber QoE over network performance indicators.

This solution makes use of the information that mobile operators are already collecting about every subscriber. This information can be used to understand LTE traffic profiles, where subscribers use their mobile phones, what services they’re using and when they’re most likely to connect from their phones. Subscriber data can also encompass LTE call traces and network configuration and drive test data to accurately identify the root causes of performance problems.

Direction Sign By doing subscriber-level network performance monitoring, mobile operators can better understand how LTE networks impact the subscriber experience, and identify areas of low signal strength or high market demand, which may decrease QoE. That means they can prioritize troubleshooting for problems that may impact high-value VIP subscribers, and proactively monitor for and address LTE performance issues before subscribers are affected. This is especially important for areas with VIP subscribers, as these customers can dramatically impact mobile operators’ revenue if they churn.

Many mobile operators dedicate extensive time and resources to conduct drive tests in order to ensure a high quality of service (QoS) for these customers. Subscriber-aware network performance management tools simplify this process by closely measuring 24×7 network call-trace analytics, reducing the need for drive tests.

Once mobile operators can monitor service quality at the subscriber level, rather than the network level, they can address problems with QoE before they reach subscribers and deliver the best possible LTE experience to subscribers around the world. As a result, they can promise a higher level of service for all subscribers, especially VIPs, and deliver on it.

Meet with InfoVista at this year’s LTE World Summit, in Amsterdam, on June 23rd-25th. For more information, visit www.lteworldsummit.com

Comments on: "Bringing LTE Network Performance Monitoring to the Subscriber Level" (1)

  1. nice article. Thanks. Have a look at a shot artcile on QoE from Machine Learning perspective. Including knowing how to apply predictive capabilites on log data to enchance QoE. http://bit.ly/1FQsIEF

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )


Connecting to %s

Tag Cloud

%d bloggers like this: