Today, cellular networks rely on fixed collections of cells (tracking areas) for handset localisation. This management parameter is manually configured and maintained and is not regularly adapted to changes in use patterns. We present a decentralised approach to localisation, based on a self-adaptive probabilistic mobility model. Estimates of model parameters are built from observations of mobility patterns collected on- line using a distributed algorithm. Based on these estimates, dynamic local neighbourhoods of cells are formed and maintained by the mobility management entities of the network. These neighbourhoods replace the static tracking areas used in current implementations by using the tracking area list facility of LTE. The model is also used to derive a multi phase paging scheme, where the division of cells into consecutive phases is optimal with respect to a set balance between response times and paging cost. The approach requires no manual tracking area configuration, and performs localisation efficiently in terms of number of location updates, page messages per localisation request and response times.