Analyzing coverage holes in mobile networks is still an important problem that needs to be addressed, mainly in Long-Term Evolution (LTE) networks, which have been recently deployed. However, each type of coverage hole has to be handled depending on the effect they have on the users. In particular, they are characterized by causing abnormal disconnections or inter-Radio Access Technology (RAT) handovers when there is an underlying RAT available to maintain the connection released by the LTE

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... ork at the cost of reducing the service performance. Therefore, in this paper, an approach to detect cells with coverage holes and diagnose their type and severity is proposed. Furthermore, this paper proposes a method capable of analyzing the impact each coverage hole has on the users both in LTE and in the underlying RAT at the same time. To that end, it performs an inter-technology follow-up of those users that leave LTE technology to continue their services in the underlying RAT and then quantifies the effect of the coverage hole by means of a new inter-technology indicator estimated from the mobile traces of both RATs. The proposed system has been validated using data from a live LTE network and its co-located 3G network, showing its effectiveness in detecting coverage holes and diagnosing their type.