Mobile coverage has traditionally been expressed in terms of geographical or population coverage but we're evolving the standard to a metric that better represents coverage in the way that users experience it: the proportion of time they have coverage.
Geographical coverage is perhaps the most traditional 'coverage' metric. This refers to the proportion of land covered by a network and is generally based on perdictive models. One of the biggest problems with describing coverage in this way is that it doesn't take into account where people are. You might have a small proportion of the land covered but it might be most of the population.
Generally this is expressed in terms of the percentage of households that have coverage. This does take into account where people but live but if fails on two counts: Firstly, it generally only accounts for coverage to the doorstep but doesn't analyse if people have coverage indoors, or the effects of building matierals. Secondly, it doesn't take into account whether people have coverage all the time they are not at home, which is a very large part of 'mobile' usage.
OpenSignal's 'Time Coverage' measures the proportion of time users have coverage. By continually measuring whether users have coverage or not we are able to extend the definition of coverage to account for what happens when users are indoors and when they are moving around. We build up a wholistic, user-centric measurmement of coverage that expresses coverage in the way that users experience it.
The OpenSignal app takes a background reading from the device every 10-15 minutes. This reading includes many fields, such as the the network technology - 2G, 3G or 4G, and we use this to calculate the proportion of time that a user has access to signal. We also measure the proportion of time a user doesn’t have access to any of these technologies, reported with the metric "Time with No Signal”.
The proportion of time on a given network type is then defined as the number of measurements on that network type, divided by the total number of measurements. We first calculate averages per device, and then average these results to give the carrier level time on LTE percentage. We use device averages to eliminate the effects of an unusual behavior profile from a device contributing a large amount of data.
Many people have LTE compatible phones, but do not have a plan which allows them to use LTE on their network. For this reason we look at all the data at the device level, and only calculate the time on LTE for a given device after we have verified that they have connected to LTE successfully at least once. This ensures that our time on LTE metric only takes in to account LTE compatible devices with an LTE compatible plan.