Can crowdsensing beat dynamic cell-ID?

In this work we investigate the limits of crowdsensing in discovering the mapping of mobile network Cell-IDs to geographic locations. We employ original large-scale mobility simulations, derived using the NRC-Lausanne dataset, to determine the fraction of cells visited by a fixed number of users over a time interval. This is vital to judge the ability of crowdsensing to rapidly update an inadequate, malfunctioning or obsolete Cell-ID database, thus preventing mechanisms such as Dynamic Cell-ID from obfuscating the network. We show that crowdsensing is quite a powerful tool, with for example only 25% more users than cells sufficing to scan 99% of the network over a day.