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they use and rely on it day in and day out to communicate. It’s no wonder that carriers try to entice customers with all those colorful coverage maps and clever commercials that they generate post-testing. However, with so many con icting research reports and with every network touting itself as number one, it’s critical that wireless carriers are transparent about how and what they actually test. If what was tested doesn’t match up with the average consumer experience, then was that test truly worthwhile?
Consider recent research Global Wireless Solutions commissioned, in an era full of texting and streaming video, voice still ranks as one of the most popular uses of mobile phones today. However, testing voice on wireless networks can be more involved than testing data speeds which perhaps is one reason why many research reports and claims only focus on data performance. To properly determine a consumer’s experience
with the network’s voice quality, benchmarking equipment utilizing standard call tests and algorithms must be deployed so that key voice metrics such as Mean Opinion Score and Perceptual Objective Listening Quality Analysis can be determined. If it sounds complicated,
it’s because it is and that’s why it’s crucial to understand the two camps of network testing – app testing and benchmark testing – and the pros and cons of each method. e test data collected is what drives report ndings and subsequent network claims; but data is malleable. e strength in a network’s claim comes from how that data was collected. To gauge the accuracy
of these claims, consumers, analysts and other stakeholders need to know what is happening behind the scenes during the testing process.
TWO TESTING CAMPS
When a carrier needs a quick glance at how
well a network is performing in certain areas they o en turn towards the rst type of testing
– app testing. is can take place through either uncontrolled crowdsource testing or controlled app testing. In short, these methods are conducted through an app that is downloaded to a user’s phone; users either initiate a test of the network themselves or the app’s background agent collects data discreetly on its own. If this is done on enough phones a carrier can get a quick pulse on performance with minimal spend.
However, uncontrolled app testing is a shallow analysis of a network – and unfortunately the methodology most likely to have been deployed in many of the reports making bold claims.
It can churn out basic performance data and provides the easiest way to interpret as best suits the carrier’s interests. It’s also fraught with many random variables that can skew the results; variables such as data collected at di erent locations on the network at di erent times using multiple devices or even similar devices with di erent rmware and operating systems. Controlled app testing improves credibility signi cantly as a trained specialist controls
and monitors a constant stream of data over
a set period of time. It’s a solid methodology
if a carrier wants to get a snapshot of how the network is performing in a speci c location
like a stadium or train station. ink average and maximum throughputs, along with signal levels and quality, task success rates, channel information across voice and data networks, and voice call drops and blocks. However, taking a snapshot only results in a general diagnosis of network performance. To truly measure and understand both data and voice performances, nd core issues, and ascertain optimal operating conditions detailed, exhaustive method of analysis would be conducted via the second camp, controlled benchmarking testing, which will be the focus of the follow up article. In the meantime, keep an eye on the numerous reports coming out declaring X network is #1 and use a critical eye to start thinking about exactly how they came to determine that! ■
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