the control plane protocols report success codes, in case of e.g. a service failure, but the user plane is seriously degrading customer experience (and the event is not considered as failure by the FM/PM system);
the counters based on time aggregated data are unable to detect abnormal behaviour due to inappropriate threshold sensitivity or time resolution;
issues impact only a specific subset of subscribers, but the given dimensions are not available as drilldown dimensions for the specific counter in the FM system;
counters refer to a single node or network element and the issue can be detected by multiple events from more NEs, i.e. impact of an issue is specific for a segment of the network identified by cross-domain dimensions (e.g. device specific being unknown for the FM counters).
It can detect network or terminal related issues which affect only a limited number of users, a limited area and/or a limited number of network elements, and the quality issues do not appear in protocol or signalling messages.
Thus, as noted above, to detect soft drop incidents, both user- and control-related metrics must be correlated. FIG. 1 illustrates an exemplary network architecture to which the techniques described herein can be applied. It will be appreciated that while FIG. 1 illustrates part of a 5G network and a 4G or 5G radio access network (RAN), the techniques described herein are applicable to other types of network (e.g. 2G and 3G networks) where soft drops may occur.