Ever been in a situation where you have four full bars but can’t make a call? I have, and that’s what made me realize that signal strength is but one of many factors that affect connectivity. Fancy wireless techniques like spatial beam forming and frame aggregation between the cell tower and the phone sounds really cool but if the network is congested at the back end then magic on the radio side won’t amount to much for the user.
One of the major challenges faced by operators is how to best manage congestion on their existing 3G network. Both AT&T and Verizon have built out a large 3G infrastructure, and at the same time are racing to provide consumers with a faster option with the new (and currently less congested) 4G LTE networks. Operators openly admit that the real problem they are trying to solve with 4G is not speed but capacity or congestion.
At a recent LTE conference I attended, an executive at Verizon explained how they plan to switch over some of their top bandwidth-hogging customers off the 3G network and onto 4G at no extra cost to the end user. Those lucky users would still have the same bandwidth caps but now operate on a relatively light or less loaded infrastructure. At the very least they would like to get the user onto WiFi or other less expensive access technologies. (a.k.a mobile data offloading)
The key to avoiding these congestion issues lies in understanding the changing nature of the traffic on the network and designing for flexibility and resilience. Traffic patterns on the network show huge variations, and are affected by many factors including:
- The number of subscribers and their activity levels
- The types of applications used
- The types of handsets used
- The amount of bandwidth consumed
- The regional or geographic location of subscribers
- The time of day, time of month, time of year
An operator with a good handle on the usage patterns and end user profiles is not only able to better manage the limited network resources, but also provide a better end user experience. In order to do this effectively, the operator needs to have good visibility into the traffic on their network. They need to understand the mix of applications and user behavior at a fundamental level. They also need to understand how their network responds and behaves under various real world conditions. Visibility gives them the ability to make intelligent policy decisions at the network level.
Providing this visibility is a key aspect of the value proposition of most, if not all, the major telecom equipment makers including Nokia Siemens Networks, Alcatel Lucent, Cisco and Ericsson. At Mu Dynamics we help the operator and equipment maker to recreate real applications and user scenarios on the 4G LTE network so that they can test their application detection capabilities as if real users were accessing these apps. With thousands of ready-to-run tests available on Mu TestCloud, to recreate popular apps like Facebook, YouTube, Netflix and Skype, these customers can simulate the affects of millions of users running a mix of applications over the LTE network. After they determine that the detection is accurate they can also model the usage patterns they see on the live network. That enables them to get closer to their goals of enforcing application level control on existing IP transport networks, helping hem analyze, optimize, secure, meter, and control all traffic flows, including content-based services and thereby mitigate congestion.
So here’s to hoping that the next time you see four bars and can’t make the call, you might get magically upgraded to the 4G LTE network. If not then at the very least the network should be smart enough to get that important call through even if it means your neighbor’s Pandora music stream gets a bit more choppy than usual.